Characteristics of the severe March 2021 Gobi Desert dust storm and its impact on air pollution in China

As the main source of dust in Asia, China often suffers from dust events. The temporal and spatial characteristics of dust events change with the variations of geography, climate and human activities. Based on the criteria of selecting dust events proposed recently by the China Environmental Monitoring Station, the hourly concentration of PM10 and PM2.5 of 336 cities in China from 2015 to 2020 were used to study the temporal and spatial characteristics of dust events more accurately and objectively. The results showed that all of the dust events in China clearly decreased, but the strong dust events did not decrease. There were 334 cities that had dust events except Shenzhen and Dongguan, 299 cities were seriously polluted due to dust events, 134 cities encountered dust level III and 56 cities encountered dust level IV. The high frequencies of dust events were mainly distributed in Northern China, especially in Northwest China. The dust contribution of PM10 to the cities in Northwest China was more than 10% and about 5–10% for PM2.5. The most likely month for dust was May. The starting time of dust was bimodally distributed, and the most common starting time was 10:00–11:00 BJT, followed by 22:00–23:00 BJT. According to the PSCF (Potential Source Contribution Function) results, the dust potential source contribution of different cities mainly came from the northwest, and was mainly affected by Mongolia in addition to the local dust in China. In addition, Beijing was obviously affected by dust recirculation. This study is of great significance to the improvement of the forecast of dust weather and the warning of heavy pollution caused by dust events.

Characteristics of Dust Events in China from 2015 to 2020

Classification and sources of extremely severe sandstorms mixed with haze pollution in Beijing.

Impacts of dust events on chemical characterization and associated source contributions of atmospheric particulate matter in northern China.

Dust storms have occurred frequently in northwest China and can dramatically reduce visibility and exacerbate air quality in downwind regions through long-range transport. In order to study the distribution characteristics of dust particles sizes, structures and concentrations in the process of dust storm, especially for the vertical distributions, the multi-observation platform composed of six Lidars and nine aerosol analytical instruments is first used to detect a severe dust storm event, which occurred in Northwest China on 3 May 2020. As a strong weather system process, the dust storm has achieved high intensity and wide range. When the intensity of a dust storm is at its strongest, the ratios of PM2.5 (particulate matter with diameter < 2.5 µm) and PM10 (particulate matter with diameter < 10 µm) (PM2.5/PM10) in cities examined were less than 0.2 and the extinction coefficients became greater than 1 km−1 based on Lidar observations. In addition, the growth rates of PM2.5 were higher than that of PM10. The dust particles mainly concentrated at heights of 2 km, after being transported about 200–300 km, vertical height increased by 1–2 km. Meanwhile, the dust concentration decreased markedly. Furthermore, the depolarization ratio showed that dust in the Tengger Desert was dominated by spherical particles. The linear relationships between 532 nm extinction coefficient and the concentration of PM2.5 and PM10 were found firstly and their R2 were 0.706 to 0.987. Our results could give more information for the physical schemes to simulate dust storms in specific models, which could improve the forecast of dust storms.

Detection of a Dust Storm in 2020 by a Multi-Observation Platform over the Northwest China

Characteristics of volatile organic compounds and secondary organic aerosol pollution in different functional areas of petrochemical industrial cities in Northwest China.

In order to improve the accuracy of dust storm prediction and reduce the damage and losses by a dust storm event, it is necessary to conduct an in-depth study on the same. The data of the national air quality stations, backward trajectories generated by the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), and the lidar network data from Wuwei, Baiyin, and Dingxi were used to study a large-scale dust storm event that occurred from 12 to 14 May 2019. This study explores the cause of the dust storm and physical characteristics of dust aerosols in three-dimensional space, as well as its impact on air quality. Results show that the dust storm was caused by the eastward movement of the East Asian trough and affected most cities in northern China from northwest to southeast. Consequently, the air quality deteriorated seriously, especially over the Hexi Corridor. The hourly peak concentrations of PM10 in Wuwei and Baiyin were close to 3,000 μg·m−3. The observations from the lidar network show that the dust intensities were similar at different cities, and their extinction coefficients were close. However, the depolarization ratio varied with sources and the physical characteristics of dust particles. According to the simulation results of extinction coefficients and particle concentrations, due to the impact of dust transported at high altitudes, the concentration of particles in Dingxi did not decrease with the increase in altitude. The particle concentrations from ground-based monitoring were lower than those of Baiyin and Wuwei, while particle concentrations above 0.3 km were higher than those of Baiyin and Wuwei.

/pdf/comprehensive-analysis-of-a-dust-storm-by-a-lidar-network-2o8fmkha.pdf

Comprehensive Analysis of a Dust Storm by a Lidar Network Combined With Multiple Data

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Lina Wang

Author Tools

Chat about Author

Papers

Characteristics of Dust Events in China from 2015 to 2020

Detection of a Dust Storm in 2020 by a Multi-Observation Platform over the Northwest China

Characteristics of volatile organic compounds and secondary organic aerosol pollution in different functional areas of petrochemical industrial cities in Northwest China.

Comprehensive Analysis of a Dust Storm by a Lidar Network Combined With Multiple Data