scholarly journals Research on the Temporal and Spatial Characteristics of Air Pollutants in Sichuan Basin

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1504
Author(s):  
Chunsheng Fang ◽  
Xiaodong Tan ◽  
Yue Zhong ◽  
Ju Wang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Sichuan Basin ◽  
Fine Particulate Matter ◽  
Weather Conditions ◽  
High Concentration ◽  
Secondary Sources ◽  
The Government ◽  
Pm2.5 And Pm10

Sichuan Basin is one of the most densely populated areas in China and the world. Human activities have great impact on the air quality. In order to understand the characteristics of overall air pollutants in Sichuan Basin in recent years, we analyzed the concentrations of six air pollutants monitored in 22 cities during the period from January 2015 to December 2020. During the study period, the annual average concentrations of CO, NO2, SO2, PM2.5 and PM10 all showed a clear downward trend, while the ozone concentration was slowly increasing. The spatial patterns of CO and SO2 were similar. High-concentration areas were mainly located in the western plateau of Sichuan Basin, while the concentrations of NO2 and particulate matter were more prominent in the urban agglomerations inside the basin. During the study period, changes of the monthly average concentrations for pollutants (except for O3) conformed to the U-shaped pattern, with the highest in winter and the lowest in summer. In the southern cities of the basin, secondary sources had a higher contribution to the generation of fine particulate matter, while in large cities inside the basin, such as Chengdu and Chongqing, air pollution had a strong correlation with automobile exhaust emissions. The heavy pollution incidents observed in the winter of 2017 were mainly caused by the surrounding plateau terrain with typical stagnant weather conditions. This finding was also supported by the backward trajectory analysis, which showed that the air masses arrived in Chengdu were mainly from the western plateau area of the basin. The results of this study will provide a basis for the government to take measures to improve the air quality in Sichuan Basin.

scholarly journals Particulate matter concentrations during winter seasons of 2016-2020 in Ulaanbaatar, Mongolia

2021 ◽  
pp. 30-39
Author(s):  
Ganzorig Byambajav ◽  
Bayarmaa Batbaatar ◽  
Ariundelger Ariunsaikhan ◽  
Sonomdagva Chonokhuu
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Single Point ◽  
Fine Particulate Matter ◽  
Measurement Data ◽  
Central Area ◽  
National Standards ◽  
Fine Particulate ◽  
The Government ◽  
Pm2.5 Concentration

In this study, we have focused on the outdoor concentration of fine particulate matter (PM2.5) during the coldest months (November-February) of 2016-2019 and January-February of 2020 and illustrated the daily, monthly and quarterly averages according to the single-point measurement data collected by the PM2.5 sensor at an air quality monitoring station located in a central area of Ulaanbaatar. The study also analyzes monthly high, low, average and median points of PM2.5 concentrations in the area that was selected. The PM2.5 sensor collects its data at an interval of every ten seconds, registers 8500 data in one day and presents the concentration of fine particulate matter in micrograms per cubic meter (μg/m3). On the basis of data collection and analysis, from November through February of 2019-2020, average PM2.5 concentration dropped noticeably by 44 per cent compared to the previous years. The Government of Mongolia took immediate action to combat air pollution of Ulaanbaatar city in May 2019 by banning the burning of raw coal in the ger districts, which account for 70 per cent of the city’s emissions, and introduced coal briquette as the only type of fuel that was allowed to be burned in metal stoves as a primary source of heating and cooking. Our study reveals that the latest government regulation had a considerable impact on air quality during winter 2019-2020 and helped in the sudden decline of the most dangerous pollutant PM2.5 concentration very close to national standards (50 µg/m3 24-hour mean) within 6 months since the enforcement of the new regulation.

SMOG IN BIALYSTOK IN POLAND. DATA OF PM 2.5 AND PM 10 PARTICULATE MATTER IN OUTDOOR AIR MEASURED IN 2017-2018 BY "THE LABORATORY OF ENERGY-EFFICIENT ARCHITECTURE AND RENEWABLE ENERGIES" AT FACULTY OF ARCHITECTURE OF BIALYSTOK UNIVERSITY OF TECHNOLOGY

2020 ◽  
Author(s):  
Adam Turecki
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Energy Efficient ◽  
Quality Index ◽  
Renewable Energies ◽  
Air Quality Index ◽  
University Of Technology ◽  
Energy Efficient Architecture ◽  
The Government ◽  
Pm2.5 And Pm10

The differences between what in the winter 2017 was presented by the government measurement station of air quality, belonging to the Chief Inspectorate of Environmental Protection (CIEP) in Bialystok in Poland, and what the citizens could see and smell, were the reason for installing the monitoring system of PM10 and PM2.5 particulate matter, in the "Laboratory of Energy-efficient Architecture and Renewable Energies" (LEARE) at the Faculty of Architecture of Bialystok University of Technology. The measurements were compared with done by CIEP and the information of “The World Air Quality Index” (WAQI). This project started in 2007. It is proving a transparent Air Quality information for more than 70 countries, covering more than 9000 stations in 600 major cities. Since 16 Nov 2017, data was also downloaded from the new European Air Quality Index (EAQI) website, created by the European Environment Agency (EEA). From the beginning of 2018, data from the public-private service AIRLY was added to the study. They installed four online dust meters in Bialystok. The density of the dust measurement network was still insufficient, so the mobile measurements were started. Recently, the use of a drone equipped with a dust meter for tests at various heights has begun. Measurements denies EAQI presentation of so good air quality in Bialystok. The levels of PM2.5 and PM10 are often much higher than those presented by EAQI and CIEP. Government measuring station, located in the center of Bialystok, poorly reflect air pollution in peripheral districts.

Satellite-based observations of ground-level fine particulate matter and comparison to a regional air quality model

2020 ◽  
Author(s):  
Jana Handschuh ◽  
Frank Baier ◽  
Thilo Erbertseder ◽  
Martijn Schaap
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Optical Parameters ◽  
Fine Particulate

<p>Particulate matter and other air pollutants have become an increasing burden on the environment and human health. Especially in metropolitan and high-traffic areas, air quality is often remarkably reduced. For a better understanding of the air quality in specific areas, which is of great environment-political interest, data with high resolution in space and time is required. The combination of satellite observations and chemistry-transport-modelling has proven to give a good database for assessments and analyses of air pollution. In contrast to sample in-situ measurements, satellite observations provide area-wide coverage ​​of measurements and thus the possibility for an almost gapless mapping of actual air pollutants. For a high temporal resolution, chemistry-transport-models are needed, which calculate concentrations of specific pollutants in continuous time steps. Satellite observations can thus be used to improve model performances.</p><p>There are no direct satellite-measurements of fine particulate matter (PM2.5) but ground-level concentrations of PM2.5 can be derived from optical parameters such as aerosol optical depth (AOD). A wide range of methods for the determination of PM2.5 concentrations from AOD measurements has been developed so far, but it is still a big challenge. In this study a semi-empirical approach based on the physical relationships between meteorological and optical parameters was applied to determine a first-guess of ground-level PM2.5 concentrations for the year 2018 and the larger Germany region. Therefor AOD observations of MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the NASA Aqua satellite were used in a spatial resolution of 3km. First results showed an overestimation of ground-level aerosols and quiet low correlations with in-situ station measurements from the European Environmental Agency (EEA). To improve the results, correction factors were calculated using the coefficients of linear regression between satellite-based and in-situ measured particulate matter concentrations. Spatial and seasonal dependencies were taken into account with it. Correlations between satellite and in-situ measurements could be improved applying this method.</p><p>The MODIS 3km AOD product was found to be a good base for area-wide calculations of ground-level PM2.5 concentrations. First comparisons to the calculated PM2.5 concentrations from chemistry-transport-model POLYPHEMUS/DLR showed significant differences though. Satellite observations will now be used to improve the general model performance, first by helping to find and understand regional and temporal dependencies in the differences. As part of the German project S-VELD funded by the Federal Ministry of Transport and Digital Infrastructure BMVI, it will help for example to adjust the derivation of particle emissions within the model.</p>

scholarly journals Studying the effect of particulate matter as SARS-CoV-2 transmitters

2021 ◽  
Author(s):  
Abdulrahim R. Hakami ◽  
Gasim Dobie
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Indirect Effects ◽  
Air Pollutants ◽  
Quality Index ◽  
Fine Particulate Matter ◽  
Future Studies ◽  
Fine Particulate ◽  
Difficult Time

Background: Studies of risk factors are especially valuable at this difficult time in the midst of a pandemic. High levels of particulate matter (PM) represent a serious risk factor on health. While this is a direct impact on health, indirect effects are worth considering too.Design and Methods: The aim of this study was to investigate the role of PM in the transmission of viruses, especially SARS-CoV-2. Also, we sought to understand dynamics of PM in still air at high and low altitudes. Historic AQI and physical PM measurements were collected between August and September 2020 using air quality detector. Potential correlations between the number of total confirmed COVID-19 cases and average air quality index (AQI) from varied geographic locations were also assessed.Results: Airborne PM levels were weakly associated with COVID-19 cases after analysing 77 territories. PM remained longer in the air at high altitudes compared to measurements made at sea level. This suggests that the link between PM and COVID-19 transmission could be aggravated in areas of high altitude.Conclusions: This article highlights that particulate matter can be involved in SARS-CoV-2 transmission. However, confounding factors may have impacted the association between the two variables. These findings can serve as a foundation for future studies on the effect of air pollutants and fine particulate matter on viral transmission.

scholarly journals Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

2019 ◽  
Author(s):  
Xue Qiao ◽  
Hao Guo ◽  
Ya Tang ◽  
Pengfei Wang ◽  
Wenye Deng ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Pollutants ◽  
Sichuan Basin ◽  
Fine Particulate Matter ◽  
Inorganic Aerosols ◽  
Multi Scale ◽  
Fine Particulate ◽  
Non Local ◽  
The Sichuan Basin ◽  
Local Emissions

Abstract. The Sichuan Basin (SCB) is one of the regions suffering from severe air pollution in China, but fewer studies have been conducted for this region than the more developed regions in North and East China. In this study, a source-oriented version of the Community Multi-scale Air Quality (CMAQ) model was used to quantify contributions from nine regions to PM2.5 (i.e., particulate matter (PM) with an aerodynamic diameter less than 2.5 μm) and its components in the 18 cities within the SCB in the winter (December 2014 to February 2015) and summer (June to August, 2015). In the winter, citywide average PM2.5 concentrations are 45~126 μg m−3, with 21~51 % and 39~66 % due to local and non-local emissions, respectively. In the summer, 15~45 % and 25~52 % of citywide average PM2.5 (14~31 μg m−3) are due to local and non-local emissions, respectively. Compared to primary PM (PPM), the inter-region transport of secondary inorganic aerosols (SIA, including ammonia (NH4+), nitrate (NO3−), and sulfate (SO42−)) is greater. The region to the east of SCB (R7) is the largest contributor outside the SCB, and it can contribute approximately 80 % in the northeast, east, and southeast rims of the SCB, but only 10 % in the other regions in both seasons. Under favorable transport conditions, regional transport of air pollutants from R7 could account for up to 35~100 μg m−3 of PM2.5 in each of the SCB cities in the winter. This study demonstrates that it is important to have joint emission control efforts among cities within the SCB and neighbor regions to the east in order to reduce PM2.5 concentrations and prevent high PM2.5 days for the entire basin.

scholarly journals Health Implications of Air Quality Index of Fine and Coarse Particulates During Outdoor Combustion of Biomass in the Niger Delta, Nigeria

2021 ◽  
pp. 21-26
Author(s):  
Glory Richard ◽  
Wisdom Ebiye Sawyer ◽  
Sylvester Chibueze Izah
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Niger Delta ◽  
Quality Index ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Air Quality Index ◽  
World Health ◽  
Health Implications ◽  
Pm2.5 And Pm10

Rural dwellers in the Niger Delta commonly use biomass for cooking and other activities. This study investigated the air quality index of fine particulate matter 2.5 (PM2.5) and coarse particulate matter 10 (PM10) and its health implications during outdoor combustion of fuelwood in the Niger Delta, Nigeria. A mini-volume air sampler (model: AEROCET 531) was used to measure PM2.5, PM10, and total suspended particulate (TSP) in the study area. A bimonthly triplicate sampling was carried out at 3 distances in 4 different states spanning one Calendar year. The results showed that PM2.5, PM10, and TSP ranged from 19.85 – 27.95µg/m3, 55.66 – 80.59µg/m3, and 74.29 – 140.44µg/m3, respectively. There was statistical variation across the different months, locations and distances, and their interactions. The concentration of PM2.5 and PM10 occasionally exceeds the World Health Organization limits of 25µg/m3 and 50µg/m3 for 24-hourly average, respectively. The air quality index showed no contamination to slight contamination in both seasons. The air quality index indicates that the air is slightly contaminated at the emission source which decreased as distance away increased. Therefore, there is a need for the regulatory agencies to consider PM2.5 and PM10 in the monitoring of ambient air quality to forestall potential hazards associated with human exposure.

scholarly journals Spatial Analysis (Measurements at Heights of 10 m and 20 m above Ground Level) of the Concentrations of Particulate Matter (PM10, PM2.5, and PM1.0) and Gaseous Pollutants (H2S) on the University Campus: A Case Study

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 62
Author(s):  
Robert Cichowicz ◽  
Maciej Dobrzański
Keyword(s):  
Spatial Distribution ◽  
Hydrogen Sulfide ◽  
Particulate Matter ◽  
Air Quality ◽  
Spatial Analysis ◽  
Ground Level ◽  
Leeward Side ◽  
High Concentration ◽  
Above Ground Level ◽  
High Concentrations

Spatial analysis of the distribution of particulate matter PM10, PM2.5, PM1.0, and hydrogen sulfide (H2S) gas pollution was performed in the area around a university library building. The reasons for the subject matter were reports related to the perceptible odor characteristic of hydrogen sulfide and a general poor assessment of air quality by employees and students. Due to the area of analysis, it was decided to perform measurements at two heights, 10 m and 20 m above ground level, using measuring equipment attached to a DJI Matrice 600 unmanned aerial vehicle (UAV). The aim of the measurements was air quality assessment and investigate the convergence of the theory of air flow around the building with the spatial distribution of air pollutants. Considerable differences of up to 63% were observed in the concentrations of pollutants measured around the building, especially between opposite sides, depending on the direction of the wind. To explain these differences, the theory of aerodynamics was applied to visualize the probable airflow in the direction of the wind. A strong convergence was observed between the aerodynamic model and the spatial distribution of pollutants. This was evidenced by the high concentrations of dust in the areas of strong turbulence at the edges of the building and on the leeward side. The accumulation of pollutants was also clearly noticeable in these locations. A high concentration of H2S was recorded around the library building on the side of the car park. On the other hand, the air turbulence around the building dispersed the gas pollution, causing the concentration of H2S to drop on the leeward side. It was confirmed that in some analyzed areas the permissible concentration of H2S was exceeded.

scholarly journals Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015–2018

2021 ◽  
Vol 18 (9) ◽  
pp. 4524
Author(s):  
Zhiyuan Wang ◽  
Xiaoyi Shi ◽  
Chunhua Pan ◽  
Sisi Wang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Large Scale ◽  
Asian Summer Monsoon ◽  
Eastern China ◽  
Climatic Conditions ◽  
Uniform Structure ◽  
Concentration Limit ◽  
Environmental Air

Exploring the relationship between environmental air quality (EAQ) and climatic conditions on a large scale can help better understand the main distribution characteristics and the mechanisms of EAQ in China, which is significant for the implementation of policies of joint prevention and control of regional air pollution. In this study, we used the concentrations of six conventional air pollutants, i.e., carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5), coarse particulate matter (PM10), and ozone (O3), derived from about 1300 monitoring sites in eastern China (EC) from January 2015 to December 2018. Exploiting the grading concentration limit (GB3095-2012) of various pollutants in China, we also calculated the monthly average air quality index (AQI) in EC. The results show that, generally, the EAQ has improved in all seasons in EC from 2015 to 2018. In particular, the concentrations of conventional air pollutants, such as CO, SO2, and NO2, have been decreasing year by year. However, the concentrations of particulate matter, such as PM2.5 and PM10, have changed little, and the O3 concentration increased from 2015 to 2018. Empirical mode decomposition (EOF) was used to analyze the major patterns of AQI in EC. The first mode (EOF1) was characterized by a uniform structure in AQI over EC. These phenomena are due to the precipitation variability associated with the East Asian summer monsoon (EASM), referred to as the “summer–winter” pattern. The second EOF mode (EOF2) showed that the AQI over EC is a north–south dipole pattern, which is bound by the Qinling Mountains and Huaihe River (about 35° N). The EOF2 is mainly caused by seasonal variations of the mixed concentration of PM2.5 and O3. Associated with EOF2, the Mongolia–Siberian High influences the AQI variation over northern EC by dominating the low-level winds (10 m and 850 hPa) in autumn and winter, and precipitation affects the AQI variation over southern EC in spring and summer.

scholarly journals Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research

2021 ◽  
Vol 13 (15) ◽  
pp. 2981
Author(s):  
Jeanné le Roux ◽  
Sundar Christopher ◽  
Manil Maskey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
Spectral Response ◽  
Fine Particulate Matter ◽  
Daily Basis ◽  
Land Cover Types ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Geolocation Accuracy

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.

scholarly journals Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Information Dissemination ◽  
Fine Particulate Matter ◽  
Model Errors ◽  
Air Quality Forecast ◽  
Fine Particulate ◽  
Regional Air Quality ◽  
Forecasting System ◽  
Air Quality Forecasting

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.

Sign in / Sign up

Export Citation Format

Share Document