scholarly journals Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air Quality in Beijing, China

2021 ◽  
Author(s):  
Benjamin Foreback ◽  
Lubna Dada ◽  
Kaspar Dällenbach ◽  
Chao Yan ◽  
Lili Wang ◽  
...  
Keyword(s):  
Air Quality ◽  
Sulfur Dioxide ◽  
Sulfuric Acid Concentration ◽  
Quality Measurement ◽  
Air Pollutant ◽  
Chinese Government ◽  
Pollution Levels ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
Spectrometer Data

Abstract. We investigated the influence of the Chinese New Year (CNY) celebrations on local air quality in Beijing from 2013 through 2019, bringing together comprehensive observations at the newly-constructed Aerosol and Haze Laboratory at Beijing University of Chemical Technology – West Campus (BUCT-AHL) and data from Chinese government air quality measurement stations. In this study, these datasets are used together to provide a detailed analysis of air quality during the CNY over multiple years. Before CNY in 2018, the city of Beijing prohibited the use of fireworks and firecrackers in an effort to reduce air pollution. In 2018 air pollutant concentrations still showed a significant peak during the CNY night, even though not as strong as in previous years, but in 2019, the pollution levels were notably lower. During the studied 7-year study period, it appears that there has been a long-term decrease in CNY related emissions since 2016. Based on our analysis, the pollutants with the most notable spike during CNY were sulfur dioxide and particulate matter, including black carbon. Sulfuric acid concentration followed the sulfur dioxide concentration and showed elevated overnight concentration in CNY 2018, but not notably in 2019. Additionally, spectrometer data and analysis of aerosol particle number size distribution shows direct emissions of particles with diameters around 20 nm during CNY in 2018 and 2019. Meteorological conditions were comparable between the latest two years, indicating that air quality associated with the CNY may be improving, perhaps a positive effect of the restrictions. The longer observations in the future will provide confirmation for these trends.

scholarly journals La surveillance de la qualité de l'air dans les Hauts-de-France

2021 ◽  
pp. 045
Author(s):  
Jimmy Leyes ◽  
Laure Roussel
Keyword(s):  
Air Quality ◽  
Air Pollutant ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Non Profit ◽  
The Public ◽  
Pollutant Concentrations ◽  
Ambient Concentrations ◽  
Air Pollutant Concentrations ◽  
Qualité De L’Air

La surveillance réglementaire de la qualité de l'air en France est confiée aux associations régionales agréées de surveillance de la qualité de l'air (Aasqa) telles qu'Atmo Hauts-de-France. Elles s'appuient sur une palette d'outils et leur expertise pour mesurer les polluants dans l'air de leur territoire, alerter les populations en cas d'épisode de pollution, répondre aux exigences réglementaires de surveillance définies au niveau européen, tout en prenant en compte les spécificités régionales. Cet article présente les différents outils utilisés par les Aasqa, et plus particulièrement Atmo Hauts-de-France, pour surveiller et estimer la qualité de l'air. L'association régionale opère ainsi un ensemble de stations de mesures fixes et mobiles pour suivre en continu les concentrations de polluants réglementés ou non sur son territoire, et dispose d'outils de modélisation pour évaluer et prévoir la qualité de l'air en tous points de la région. Cet article présente également certains des paramètres météorologiques qui influencent la qualité de l'air de la région Hauts-de-France, particulièrement concernée par les épisodes de pollution aux particules. Regulatory air quality monitoring in France is performed by government-approved non-profit organisations called AASQAs, one of which is Atmo Hauts-de-France. These organisations rely on decades of accumulated air quality expertise and use several techniques to measure air pollutant concentrations, inform the public when pollutant levels are unhealthy, and comply with E.U. air quality monitoring regulations. This paper gives an overview of the tools used by AASQAs, and more particularly by Atmo Hauts-de-France, to monitor and forecast air quality. The year-round continuous monitoring of air pollutant levels at fixed sites is supplemented by short-term measurements made with fully-equipped vehicles or trailers and by modelling tools that forecast air quality and estimate pollutant levels where there are no measurements. AASQAs study pollutants which ambient concentrations are regulated by European air quality standards as well as other pollutants which are not regulated in this way. This work also discusses some of the meteorological factors, that affect air quality in the region Hauts-de-France, which is heavily impacted by particulate matter pollution.

scholarly journals Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal

2019 ◽  
Vol 19 (12) ◽  
pp. 8209-8228 ◽  
Author(s):  
Min Zhong ◽  
Eri Saikawa ◽  
Alexander Avramov ◽  
Chen Chen ◽  
Boya Sun ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Air Pollutant ◽  
Kathmandu Valley ◽  
So2 Emissions ◽  
Emissions Inventory ◽  
Brick Kilns ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
Local Emissions

Abstract. Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emissions (IVE) model with local emissions factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emissions factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. HTAP_v2.2 does not include the brick sector and we found that our sulfur dioxide (SO2) emissions estimates from brick kilns are comparable to 70 % of the total SO2 emissions considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emissions scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model's boundary-layer representation, to capture strong spatial gradients of air pollutant concentrations.

Land use regression modelling of ambient air pollutants in Hong Kong

2020 ◽  
Author(s):  
Zhiyuan Li ◽  
Steve Hung Lam Yim ◽  
Kin-Fai Ho
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Air Quality ◽  
Air Pollutants ◽  
Ambient Air ◽  
Air Pollutant ◽  
High Rise ◽  
Pollutant Concentrations ◽  
Air Quality Measurements ◽  
Air Pollutant Concentrations

<p>Land use regression (LUR) models estimate air pollutant concentrations for areas without air quality measurements, which provides valuable information for exposure assessment and epidemiological studies. In the present study, we developed LUR models for ambient air pollutants in Hong Kong, China, a typical high-density and high-rise city. Air quality measurements at sixteen air quality monitoring stations, operated by the Hong Kong Environmental Protection Department, were collected. Moreover, five categories of predictor variables, including population distribution, traffic emissions, land use variables, urban/building morphology, and meteorological parameters, were employed to establish the LUR models of various air pollutants. Then the spatial distribution of air pollutant concentrations at 1 km × 1 km grid cells were plotted. Taking fine particle (PM2.5) as an example, the developed LUR model explained 89% of variability of PM2.5 concentrations, with a leave-one-out-cross-validation R2 of 0.64. LUR modelling results for other air pollutants will be presented. In addition, further improvements on the development of LUR models will be discussed. This study can help to assess long-term exposures to air pollutants for high-density and high-rise urban areas like Hong Kong.</p>

scholarly journals Aggravation of CoVID-19 infections due to air pollutant concentrations in Indian cities

2021 ◽  
Author(s):  
Arnab Mondal ◽  
Asha Sunilkumar ◽  
Shishir Kumar Singh ◽  
Surajit Mondal ◽  
Amit Kumar Mondal
Keyword(s):  
Air Pollutants ◽  
Time Frame ◽  
Air Pollutant ◽  
Pollution Levels ◽  
Pollutant Concentrations ◽  
The Government ◽  
Air Pollutant Concentrations ◽  
High Level ◽  
In The Beginning ◽  
Indian Cities

Abstract In the beginning of March 2020, cases of CoVID-19 infections began rising worldwide, reacting to which the Government of India called for nationwide lockdown initially for March 25th to April 14th, 2020 and later extended it in phases till May 31st, 2020. Due to the forced restrictions pan-India on every level, the move led to drastic drop in pollution levels. The results demonstrated that during lockdown air quality is significantly improved and the pollution levels of PM2.5, PM10, SO2 and NO2 reduced drastically during the lockdown period than the preceding year for the same time frame. A direct relationship has been established between the high level of air pollutants (PM2.5, PM10, NO2 and SO2) and CoVID-19 infections being reported in these Indian cities. The correlation indicates that the air pollutants like PM2.5, PM10, NO2 and SO2 are aggravating the number of casualties due to the CoVID-19 infections. The high-level exposure of PM2.5 over a long period is found to be significantly correlated with the mortality per unit confirmed CoVID-19 cases as compared to other air pollutant parameters like PM10, NO2 and SO2.

scholarly journals Mobile-platform measurement of air pollutant concentrations in California: performance assessment, statistical methods for evaluating spatial variations, and spatial representativeness

2020 ◽  
Vol 13 (6) ◽  
pp. 3277-3301
Author(s):  
Paul A. Solomon ◽  
Dena Vallano ◽  
Melissa Lunden ◽  
Brian LaFranchi ◽  
Charles L. Blanchard ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
San Francisco ◽  
Spatial Variations ◽  
Air Pollutant ◽  
Mobile Platform ◽  
Diurnal Variability ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
Mobile Measurements

Abstract. Mobile-platform measurements provide new opportunities for characterizing spatial variations in air pollution within urban areas, identifying emission sources, and enhancing knowledge of atmospheric processes. The Aclima, Inc., mobile measurement and data acquisition platform was used to equip four Google Street View cars with research-grade instruments, two of which were available for the duration of this study. On-road measurements of air quality were made during a series of sampling campaigns between May 2016 and September 2017 at high (i.e., 1 s) temporal and spatial resolution at several California locations: Los Angeles, San Francisco, and the northern San Joaquin Valley (including nonurban roads and the cities of Tracy, Stockton, Manteca, Merced, Modesto, and Turlock). The results demonstrate that the approach is effective for quantifying spatial variations in air pollutant concentrations over measurement periods as short as 2 weeks. Measurement accuracy and precision are evaluated using results of weekly performance checks and periodic audits conducted through the sampler inlets, which show that research instruments located within stationary vehicles are capable of reliably measuring nitric oxide (NO), nitrogen dioxide (NO2), ozone (O3), methane (CH4), black carbon (BC), and particle number (PN) concentration, with bias and precision ranging from < 10 % for gases to < 25 % for BC and PN at 1 s time resolution. The quality of the mobile measurements in the ambient environment is examined by comparisons with data from an adjacent (< 9 m) stationary regulatory air quality monitoring site and by paired collocated vehicle comparisons, both stationary and driving. The mobile measurements indicate that United States Environmental Protection Agency (US EPA) classifications of two Los Angeles stationary regulatory monitors' scales of representation are appropriate. Paired time-synchronous mobile measurements are used to characterize the spatial scales of concentration variations when vehicles were separated by < 1 to 10 km. A data analysis approach is developed to characterize spatial variations while limiting the confounding influence of diurnal variability. The approach is illustrated using data from San Francisco, revealing 1 km scale differences in mean NO2 and O3 concentrations up to 117 % and 46 %, respectively, of mean values during a 2-week sampling period. In San Francisco and Los Angeles, spatial variations up to factors of 6 to 8 occur at sampling scales of 100–300 m, corresponding to 1 min averages.

scholarly journals 30 Years of Air Quality Trends in Japan

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1072
Author(s):  
Akiyoshi Ito ◽  
Shinji Wakamatsu ◽  
Tazuko Morikawa ◽  
Shinji Kobayashi
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutant ◽  
Control Measures ◽  
Related Substances ◽  
Pollutant Concentrations ◽  
Exhaust Particles ◽  
Air Pollutant Concentrations ◽  
Atmospheric Concentrations ◽  
Pollution Concentrations

The aim of this paper is to obtain information that will contribute to measures and research needed to further improve the air quality in Japan. The trends and characteristics of air pollutant concentrations, especially PM2.5, ozone, and related substances, over the past 30 years, are analyzed, and the relationships between concentrations and emissions are discussed quantitatively. We found that PM2.5 mass concentrations have decreased, with the largest reduction in elemental carbon (EC) as the PM2.5 component. The concentrations of organic carbon (OC) have not changed significantly compared to other components, suggesting that especially VOC emissions as precursors need to be reduced. In addition, the analysis of the differences in PM2.5 concentrations between the ambient and the roadside showed that further research on non-exhaust particles is needed. For NOx and SO2, there is a linear relationship between domestic anthropogenic emissions and atmospheric concentrations, indicating that emission control measures are directly effective in the reduction in concentrations. Also, recent air pollution episodes and the effect of reduced economic activity, as a consequence of COVID-19, on air pollution concentrations are summarized.

scholarly journals Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal

2018 ◽  
Author(s):  
Min Zhong ◽  
Eri Saikawa ◽  
Alexander Avramov ◽  
Chen Chen ◽  
Boya Sun ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Air Pollutant ◽  
Kathmandu Valley ◽  
Emissions Inventory ◽  
Brick Kilns ◽  
Pollutant Concentrations ◽  
Testing Experiment ◽  
Air Pollutant Concentrations ◽  
Local Emissions

Abstract. Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emission (IVE) model with local emission factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emission factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly-used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. In addition, brick kilns account for nearly 70 % of total sulfur dioxide (SO2) emissions from all sectors considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emission scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model's boundary-layer representation, to capture strong spatial gradients of air pollutant concentrations.

scholarly journals The relationship between air quality and respiratory pathogens among children in Suzhou City

2019 ◽  
Vol 45 (1) ◽  
Author(s):  
Dandan Zhang ◽  
Yuqin Li ◽  
Qiu Chen ◽  
Yanqun Jiang ◽  
Chu Chu ◽  
...  
Keyword(s):  
Air Quality ◽  
Respiratory Tract ◽  
Respiratory Tract Infections ◽  
Respiratory Infections ◽  
Age Groups ◽  
Air Pollutant ◽  
Pollutant Concentrations ◽  
Suzhou City ◽  
Air Pollutant Concentrations ◽  
Tract Infections

Abstract Objective We studied the short-term effects of air pollutant concentrations in Suzhou City on respiratory infections in children of different age groups. Methods We employed clinical data from children hospitalized with respiratory infections at the Children’s Hospital of Soochow University during 2014–2016, and air quality for Suzhou City covering the same period.We investigated the relationships between the air pollutant concentrations and respiratory tract infections in children by causative pathogen using time series models with lagged effects. Results The results of single-pollutant models showed that PM2.5, PM10, NO2, SO2 and CO had statistically significant associations with respiratory tract infections in children under 3 years, with the largest effect sizes at a lag of 3 weeks. Notably, the multi-pollutant model found PM2.5 was significantly associated with viral respiratory in children under 7 months, and bacterial respiratory infections in other age groups, while PM10 concentrations were associated with viral infections in preschool children. Conclusion PM2.5, PM10 and NO2 are the main atmospheric pollutants in Suzhou. The associations between pollutant concentrations and viral and bacterial respiratory infections were stronger among children under 3 years than for older age group.s PM2.5 had the strongest influence on viral and Mycoplasma pneumoniae respiratory infections when multiple pollutants were tested together.

scholarly journals What is the relationship between the coronavirus crisis and air pollution in Tunisia?

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Nihel Chekir ◽  
Yassine Ben Salem
Keyword(s):  
Air Quality ◽  
Sulfur Dioxide ◽  
Nitrogen Dioxide ◽  
Significant Drop ◽  
Industrial Activity ◽  
Substantial Impact ◽  
Social Distancing ◽  
Pollution Levels ◽  
Positive Side ◽  
Pollutant Concentrations

Abstract Since the beginning of 2020, the COVID-19 pandemic has generated horror and panic around the world. Nevertheless, this terrible crisis is having a positive side effect: it is lowering pollution levels. The outbreak of the coronavirus has caused many governments to impose measures to slow the spread of the virus within populations, such as limiting population displacement, requesting social distancing and the isolation of individuals at home, and reducing industrial activity. In this work, we investigated the effects of governmental measures taken to limit the spread of COVID-19 on the concentrations of air pollutants over four Tunisian cities (Tunis, Sousse, Sfax, and Tataouine). Data on the average daily levels of nitrogen dioxide, sulfur dioxide, carbon monoxide, and particulate matter during January, February, March, and April of 2020 were collected, treated, and analyzed for each city. Curves of average monthly pollutant concentrations from 1 January to 30 April for each city investigated showed that measures taken to reduce the spread of the virus had a substantial impact on emission levels: there were tremendous drops of 51% in NO2 and 52% in SO2 over Sfax City during March compared to those during January, while nitrogen dioxide and sulfur dioxide levels dropped by about 38% and 42%, respectively, over Tunis City and by around 20% for Sousse. During the four months investigated, almost all of the pollutant concentrations showed a significant drop from mid-March. On 12 March, the Tunisian government imposed some individual and collective measures to protect the population from the virus, such as social distancing, limiting transportation, shutting down schools and universities, and reducing industrial activity. A general lockdown was brought in later. Thus, restricting human and industrial activities appeared to affect the air quality in Tunisia, leading to a marked improvement in the air quality index. Graphic abstract

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