Pollution characteristics in a dusty season based on highly time-resolved online measurements in northwest China

Influence of anthropogenic activities and loess dusts on the rainwater hydrochemistry in the Chinese Loess Plateau

Rainwater hydrochemistry is an important indicator for tracing anthropogenic input on air quality. As the fastest economically developing city in the northwestern China and the Chinese Loess Plateau, rainwater chemistry, sources of dissolved solutes, and the influence of loess dust on rainwater chemistry in Xi'an city is unclear. Inorganic ions, δD and δ18O of two years' rainwater samples were measured to decipher the above issues. Rainwater samples were weakly alkaline (pH = 7.2) with the mean total dissolved solids (TDS) values of 43 mg/L. NH4+ and Ca2+ dominated in the cations and SO42- and NO3- dominated in the anions. The wet deposition of sulfur (S) and nitrogen (N) was 70.9 ± 67 mg·(m2·month)-1 and 244.8 ± 270.9 mg·(m2·month)-1, respectively. The meteoric water line in Xi'an was δD = 7.29δ18O+3.72 (R2 = 0.99). δD, δ18O, and d-excess analysis indicated the influence of evaporation on the dissolved solutes in rainwater, especially in the dry season. Rainwater acidity in the Xi'an city was mainly neutralized by Ca2+ and NH4+, and the neutralization ability in Xi'an city is higher than the southern China cities. Correlation analysis (CA), positive matrix factorization (PMF), and the backward air masses trajectory model identified high NH4+ and Ca2+ in rainwater were mainly originated from local agricultural activities and loess dust, while NO3- and SO42- were associated with local coal combustion and vehicle exhaust sources. High inputs of dusts and coal combustion in spring and winter resulted in elevated values of pH and major ions in Xi'an. Due to the air pollution control policy, air quality in Xi'an is getting better in recent years. Our study highlights the influence of anthropogenic activities and loess dusts on the rainwater hydrochemistry in Xi'an and provides important dataset for air pollution control for other cities in semi-arid and arid regions.

Evaluating city road dust emission characteristics with a dynamic method: A case study in Luoyang, China

Road dust, a significant contributor to non-exhaust particulate matter emissions in urban transport, poses considerable health risks, necessitating accurate and high-resolution data for effective control. The traditional AP-42 method offers data on point-specific dust emissions, while vehicle-based testing ascertains the relative emission intensity in the road network. However, a clear mathematical relationship between these measurements has been elusive, limiting efficiency in emission control. By integrating the On-board Conventional Pollutant Monitoring System with the AP-42 method, we devised a dynamic link between the concentration of particles in vehicle plumes and actual road dust emissions. This relationship is substantiated by a notable correlation (R2 = 0.91) between our emission factors and those calculated using the AP-42 method. Significant variations emerged in dust emission factors across road types, with changes between -30.1 % to +57.79 % from the average (0.05 g·vehicle-1·km-1), in tandem with traffic flow fluctuations of approximately ±90 %. Meteorological factors, except for continuous rainfall, showed minimal impact on dust emissions. However, our findings revealed a significant underestimation (58.87 %) of road dust PM10 emissions by the AP-42 method. Intriguingly, we found that short-range emission hotspots substantially contribute to total emissions, suggesting a potential 50 % reduction by controlling merely 8.8 % ± 2.5 % of the total road length. Our research elucidates the interplay between road dust emissions, road types, and human activities. The application of a dynamic, high-resolution assessment method enhances our understanding of the impacts of road dust on urban particulate pollution, allows accurate hotspot identification, and aids in developing efficacious strategies for air quality enhancement.

Formation of an unprecedented yellow snow episode in Xinjiang on December 1, 2018

On 1 December 2018, a heavy yellow snow fell in Urumqi (87°37'E, 43°47'N) - the largest city of northwest China's Xinjiang province, which was the first case that the yellow snow has been observed in winter. The air parcel trajectories obtained from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the dust surface mass concentration from Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) were adopted to identify the potential sources and transport paths of pollutants responsible for this yellow snow episode. The meteorological situation and the European Center for Medium-Range Weather Forecasts (ECMWF) forecast products have been utilized to analyze the supportive meteorological conditions. The results showed that the heavy snow in Urumqi was contaminated by the yellow dust originated in Karamay of Xinjiang province. The strong surface winds in Karamay lifted large amounts of dust into the atmosphere. Then the airborne dusts were transported to Urumqi rapidly by strong low-level winds, where precipitation in connection with the upper trough and the cold front lead to the yellow snow episode. This study can provide important scientific significance for predicting this kind of event (yellow snow).

Characteristics, Possible Origins, and Health Risk Assessment of Trace Elements in Surface Waters of the Han River Watershed, South Korea

To safeguard aquatic environments in and around the Han River watershed in South Korea, a multivariate statistical evaluation of trace elements, a trace element concentration analysis and source determination, and a human health risk assessment were conducted on 10 trace elements at 25 sites. The results demonstrated that the Han River watershed was mainly affected by anthropogenic activities (traffic/industrial activity). The range of concentrations was arranged in descending order: Fe (217.13 ± 301.03 µg/L) > Mn (102.36 ± 153.04 µg/L) > Zn (23.33 ± 79.63 µg/L) > Ba (29.05 ± 12.37 µg/L) > Ni (5.14 ± 11.57 µg/L) > Cu (3.80 ± 3.56 µg/L) > Pb (0.46 ± 0.52 µg/L) > Se (0.06 ± 0.04 µg/L) > Cd (0.01 ± 0.01 µg/L) > Ag (0.004 ± 0.013 µg/L). The hazard index values of trace elements in surface water for combined pathways (ingestion and dermal contact) were < 1.0 for both adults and children, indicating no possible human health hazards. The estimated total cancer risk did not exceed the acceptable limit (1 × 10^-4) for adults and children. The findings of this study provide data-driven guidelines for water environment policy decisions in the study area.

Source Apportionment of Fine Particulate Matter during the Day and Night in Lanzhou, NW China

Source apportionment of PM_2.5 in Lanzhou, China, was carried out using positive matrix factorization (PMF). Seventeen elements (Ca, Fe, K, Ti, Ba, Mn, Sr, Cd, Se, Pb, Cu, Zn, As, Ni, Co, Cr, V), water-soluble ions (Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca², Cl^-, NO₃^-, SO₄^2-), and organic carbon (OC) and elemental carbon (EC) were analyzed. The results indicated that the mean concentration of PM_2.5 was 178.63 ± 96.99 μg/m³. In winter, the PM_2.5 concentration was higher during the day than at night, and the opposite was the case in summer, and the nighttime PM_2.5 concentration was 1.3 times higher than during the day. Water-soluble ions were the dominant component of PM_2.5 during the study. PMF source analysis revealed six sources in winter, during the day and night: salt lakes, coal combustion, vehicle emissions, secondary aerosols, soil dust, and industrial emissions. In summer, eight sources during the day and night were identified: soil dust, coal combustion, industrial emissions, vehicle emissions, secondary sulfate, salt lakes, secondary aerosols, and biomass burning. Secondary aerosols, coal combustion, and vehicle emissions were the dominant sources of PM_2.5. In winter, the proportions of secondary aerosols and soil dust sources were greater during the day than at night, and the opposite was the case in summer. The coal source, industrial emissions source, and motor vehicle emissions source were greater at night than during the day in winter. This work can serve as a case study for further in-depth research on PM_2.5 pollution and source apportionment in Lanzhou, China.

Sources of PM2.5-bound water soluble ions at EMEP's Auchencorth Moss (UK) supersite revealed by 3D-Concentration Weighted Trajectory (CWT) model

The Concentration Weighted Trajectory (CWT) model is a well-known tool which combines the residence time (trajectory points) of air masses over specific regions with ambient concentrations of air pollutants, aiming to identify potential long range transport impacts. An upgraded 3D-version of CWT model (3D-CWT), investigating not only the geographical origin of the exogenous emissions but also the altitudinal layers in which the transport occurs, was developed and coupled with PM_2.5-bound concentrations of water soluble ions (nss- SO₄^-2 (non-sea salt sulfates), NO₃^-, Cl^-, NH₄⁺, Na⁺, Mg⁺², Ca⁺² and K⁺) for the years 2017-2018, derived by the Auchencorth Moss supersite in Southeast Scotland, United Kingdom (UK). The 3D-CWT model was implemented in two distinct altitudinal layers above ground level (0 m ≤ Layer 1 < 1000 m, 1000 m ≤ Layer 2 < 2000 m), because few trajectory points exceeded the 2000 m limit. Transport of Secondary Inorganic Aerosols (SIA) from South - Southeast England were detected in both vertical layers, affecting SO₄^-2, NO₃^-, and NH₄⁺ levels, whilst SIA intrusions from Northwest Europe were detected in Layer 2. Sea salt particle transport from North Atlantic and the North Sea, comprising Cl^-, Na⁺ and Mg⁺², were detected in both layers whilst K⁺ contributions from Southeast England were also detected in both layers, suggesting also impacts from biomass burning. Moreover particle transport of a crustal origin, marked by Ca⁺² enhancement, mainly occurred in layer 1 and included soil/dust resuspension from areas around the station and infrequent dust intrusions from the Sahara desert.

Water-Soluble Ions in Atmospheric Aerosol Measured in a Semi-Arid and Chemical-Industrialized City, Northwest China

We investigated water-soluble ions (WSIs) of aerosol samples collected from 2016 to 2017 in Lanzhou, a typical semi-arid and chemical-industrialized city in Northwest China. WSIs concentration was higher in the heating period (35.68 ± 19.17 μg/m3) and lower in the non-heating period (12.45 ± 4.21 μg/m3). NO3−, SO42−, NH4+ and Ca2+ were dominant WSIs. The concentration of SO42− has decreased in recent years, while the NO3− level was increasing. WSIs concentration was affected by meteorological factors. The sulfur oxidation and nitrogen oxidation ratios (SOR and NOR) exceeded 0.1, inferring the vital contribution of secondary transformation. Meanwhile higher O3 concentration and temperature promoted the homogeneous reaction of SO2. Lower temperature and high relative humidity (RH) were more suitable for heterogeneous reactions of NO2. Three-phase cluster analysis illustrated that the anthropogenic source ions and natural source ions were dominant WSIs during the heating and non-heating periods, respectively. The backward trajectory analysis and the potential source contribution function model indicated that Lanzhou was strongly influenced by the Hexi Corridor, northeastern Qinghai–Tibetan Plateau, northern Qinghai province, Inner Mongolia Plateau and its surrounding cities. This research will improve our understanding of the air quality and pollutant sources in the industrial environment.

Analysis on the Characteristics of Air Pollution in China during the COVID-19 Outbreak

The COVID-19 pandemic poses a serious global threat to human health. In China, the government immediately implemented lockdown measures to curb the spread of this virus. These measures severely affected transportation and industrial production across the country, resulting in a significant change in the concentration of air pollutants. In this study, the Euclidean distance method was used to select the most similar meteorological field during the COVID-19 lockdown period. Changes in the concentration of air pollutants in China were analyzed under similar meteorological background conditions. Results indicate that, compared with data from 2015–2019, air quality in China significantly improved; with the exception of ozone (O3), the concentration of major air pollutants declined. Compared with baseline conditions, the reduction of air pollutants in China from 25 January to 22 February 2020 (Period 2) was the most significant. In particular, NO2 decreased by 41.7% in the Yangtze River Delta. In Period 2, the reduction of air pollutants in areas other than Hubei gradually decreased, but the reduction of NO2 in Wuhan reached 61.92%, and the reduction of air pollutants in various regions after February 23 was significantly reduced. By excluding the influence of meteorological factors and calculating the contribution of human activities to atmospheric pollutants by linear fitting, in Period 2 the effect of artificial controls on NO2 in Wuhan attained 30.66%, and reached 48.17% from 23 February to 23 March (Period 3). Results from this investigation provides effective theoretical support for pollution prevention and control in China.

Air pollution characteristics and human health risks in key cities of northwest China

Air pollution events occur frequently in northwest China, which results in serious detrimental effects on human health. Therefore, it is essential to understand the air pollution characteristics and assess the risks to humans. In this study, we analyzed the pollution characteristics of criteria pollutants in six key cities in northwest China from 2015 to 2018. We used the air quality index (AQI), aggregate AQI (AAQI), and health-risk based AQI (HAQI) to assess the health risks and determine the proportion of people exposed to air pollution. Additionally, on this basis, the AirQ_2.2.3 model was used to quantify the health effects of the pollutants. The results showed that PM₁₀ pollution occurred mainly in spring and winter and was caused by frequent dust storms. PM_2.5 pollution was caused mainly by anthropogenic activities (especially coal-fired heating in winter). Because of a series of government policies and pollutant reduction measures, PM_2.5, SO₂, NO₂, and CO concentrations showed a downward trend during the study period (except for a small increase in the case of NO₂ in some years.). However, O₃ showed high concentrations due to the high intensity of solar radiation in summer and inadequate emission reduction measures. The air quality levels based on their classification were generally higher than the Chinese ambient air quality standard classified by the AQI index. We also found that the higher the AQI index was, the more serious the air pollution classified based on the AAQI and HAQI indices was. The HAQI index could better reflect the impact of pollutants on human health. Based on the HAQI index, 20% of the population in the study area was exposed to polluted air. The total mortality values attributable to PM₁₀, PM_2.5, SO₂, O₃, NO₂, and CO, quantified by the AirQ_2.2.3 model, were 3.00%, 1.02%, 1.00%, 4.22%, 1.57%, and 0.95% (Confidence Interval:95%), respectively; the attributable proportions of mortality for respiratory system and cardiovascular diseases were consistent with the change rule of total mortality, because the number of deaths attributable to the latter was greater than that for the former. According to the exposure reaction curves of pollutants, PM₁₀ and PM_2.5 still showed a large change at high concentrations. However, the tendencies of SO₂, NO₂, CO, and O₃ were more obvious under low concentration exposure, which indicated that the expected mortality rate due to lower air pollution concentrations was much higher than the mortality due to high air pollution concentrations.

Source-specific ecological risk analysis and critical source identification of heavy metals in road dust in Beijing, China

To explore the spatial variation of source-specific ecological risks and identify critical sources of heavy metals in road dust, 36 road dust samples collected in Beijing in March 2017 were analyzed for heavy metals. A new method that takes into consideration the heavy-metal toxic response and is flexible to changes in the number of calculated heavy metals, called the Nemerow integrated risk index (NIRI), was developed for ecological risk assessment. The NIRI indicated that heavy metals posed considerable to high risks at the majority of sites, and 22 % of the sites suffered extreme risk in spring (NIRI > 320). Four main sources were identified based on positive matrix factorization (PMF): traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Owing to the lower toxic response factors of representative heavy metals of fuel combustion than those of other sources, although fuel combustion had the highest contribution (34.21 %) to heavy metals in spring, it only contributed 5.57 % to ecological risks. Critical sources and critical source areas were determined by considering the contributions to both heavy metals and ecological risks. The use of pesticide and fertilizer and traffic-related exhaust were identified as critical sources of heavy metals in spring. Source-specific ecological risks and critical sources of heavy metals changed with the changing seasons, which suggests that different strategies should be adopted in different seasons.

Characteristics of Aerosol Chemical Compositions and Size Distributions during a Long-Range Dust Transport Episode in an Urban City in the Yangtze River Delta

A long- and large-range heavy dust episode occurred from 3 to 8 May 2017 in China. To explore the impacts of this long-range dust transport episode on the chemical compositions and size distributions of urban aerosols, such instruments as an online analyzer for monitoring aerosols and gases (MARGA) and a wide-range particle spectrometer (WPS) were mainly used to monitor chemical components, such as PM2.5 and aerosol size distributions in the range of 10 nm to 10 μm, in Nanjing in this study. During the dust episode, the average concentrations of PM2.5 and PM10 and ions of Ca2+, Mg2+, Cl-, SO42−, NO3−, and NH4+ were 66.2, 233.9, and 1.1, 1.5, 1.1, 11.4, 7.8 and 4.4 μg·m−3, which were 4.4, 5.8, 3.7, 15, 1.38, 1.84, 1.66 and 1.83 times higher than the values observed before the episode and 2.2, 3.3, 5.5, 5.0, 1.57, 1.97, 1.39 and 1.69 times the levels after the episode. The dusts were demonstrated to have differential impacts on the water-soluble gases in the air. During the dust episode, the concentrations of HCl, SO2 and NH3 were comparably low, while the HNO2 and HNO3 concentrations were high. The diurnal variations in pollutants, including SO2, HNO3, Cl−, Ca2+, Mg2+, PM2.5 and PM10, were strongly impacted by the dust episode. However, those variations in NH3, NO3−, SO42− and NH4+ were only slightly influenced. Pollutants were distinctively featured in the various dust stages. The concentration of HNO2 was relatively high in the earliest stage but was substituted by those of SO2, PM10, PM2.5, Ca2+, Mg2+ HNO3 and Cl- in the explosion stage. The aerosol number concentrations exhibited unimodal distributions in the earliest and explosion stages but showed bimodal distributions in the duration and dissipation stages. Additionally, the aerosol size distributions were observed to shift to larger particle segments in different dust stages. The surface area concentrations exhibited four peaks in different dust stages and exhibited trimodal distributions in the non-dust episode. The surface area concentration of fine particles first increased during the earliest stage, while that of coarse particles first decreased during the dissipation stage.