scholarly journals The Aerosol Research Observation Station (AEROS)

2021 ◽  
Author(s):  
Karin Ardon-Dryer ◽  
Mary C. Kelley ◽  
Xia Xueting ◽  
Yuval Dryer
Keyword(s):  
Air Quality ◽  
The United States ◽  
Atmospheric Particles ◽  
High Plains ◽  
Observation Station ◽  
West Texas ◽  
Total Particle ◽  
Dust Events ◽  
The Impact ◽  
Pollution Events

Abstract. Information on atmospheric particles’ concentration and sizes are important for environmental and human health reasons. Air quality monitor stations (AQMSs) for measuring Particulate Matter (PM) concentrations are found across the United States, but only three AQMSs measure PM2.5 concentrations (particles with an aerodynamic diameter of < 2.5 μm) in the Southern High Plains of West Texas (area ≥ 1.8 × 105 km2). This area is prone to many dust events (~21 per year), yet no information is available on other PM sizes, total particle concentration, or size distribution during these events. The Aerosol Research Observation Station (AEROS) was designed to continuously measure these particles’ concentrations to better understand the impact of dust events on local air quality. The AEROS aerosol measurements unit features a temperature-controlled shed with a dedicated inlet and custom-built dryer for each of the three aerosol instruments used. This article provides a description of AEROS as well as an intercomparison of the different instruments using laboratory and atmospheric particles, which shows that the instruments used provided similar concentration measurements. Measurement with AEROS can distinguish between various pollution events (natural dust events vs anthropogenic haze) to improve knowledge of the air quality in this region.

Assessing the impact of Chinese FY-3/MERSI AOD data assimilation on air quality forecasts: Sand dust events in northeast China

2019 ◽  
Vol 205 ◽  
pp. 78-89 ◽  
Author(s):  
Yansong Bao ◽  
Liuhua Zhu ◽  
Qin Guan ◽  
Yuanhong Guan ◽  
Qifeng Lu ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Northeast China ◽  
Dust Events ◽  
The Impact ◽  
Sand Dust

scholarly journals Megacity and local contributions to regional air pollution: An aircraft case study over London

2019 ◽  
Author(s):  
Kirsti Ashworth ◽  
Silvia Bucci ◽  
Peter J. Gallimore ◽  
Junghwa Lee ◽  
Beth S. Nelson ◽  
...  
Keyword(s):  
Air Quality ◽  
Early Career ◽  
Atmospheric Measurements ◽  
Airborne Measurements ◽  
Sources Of Pollution ◽  
Pollutant Concentrations ◽  
Local Sources ◽  
The Uk ◽  
The Impact ◽  
Pollution Events

Abstract. In July 2017 three research flights circumnavigating the megacity of London were conducted as a part of the STANCO training school for students and early career researchers organised by EUFAR (European Facility for Aircraft Research). Measurements were made from the UK’s Facility for Airborne Atmospheric Measurements (FAAM) BAe-146-301 Atmospheric Research Aircraft with the aim to sample, characterise and quantify the impact of megacity outflow pollution on air quality in the surrounding region. Conditions were extremely favourable for airborne measurements and all three flights were able to observe clear pollution events along the flight path. A small change in wind direction provided sufficiently different airmass origins over the two days such that a distinct pollution plume from London, attributable marine emissions and a double-peaked dispersed area of pollution resulting from a combination of local and transported emissions were measured. We were able to analyse the effect of London emissions on air quality in the wider region and the extent to which local sources contribute to pollution events. The background air upwind of London was relatively clean during both days; concentrations of CO were 88–95 ppbv, total (measured) volatile organic compounds (VOCs) were 1.6–1.8 ppbv, and NOx were 0.7–0.8 ppbv. Downwind of London, we encountered elevations in all species with CO > 100 ppbv, VOCs 2.8–3.8 ppbv, CH4 > 2080 ppbv and NOx > 4 ppbv, and peak concentrations in individual pollution events higher still. Levels of O3 were inversely correlated with NOx during the first flight, with O3 concentrations of 37 ppbv upwind falling to ~ 26 ppbv in the well-defined London plume. Mass balance techniques were applied to estimate pollutant fluxes from London. Our calculated CO2 fluxes are within 10 % of those estimated previously, but there was a greater disparity in our estimates of CH4 and CO. On the second day, winds were lighter and downwind O3 concentrations were elevated to ~ 39–43 ppbv (from ~ 32–35 ppbv upwind), reflecting the contribution of more aged pollution to the regional background. Elevations in pollutant concentrations were dispersed over a wider area than the first day, although we also encountered a number of clear spikes from local sources. This series of flights demonstrated that megacity outflow, local fresh emissions and more distant UK sources of pollution all contribute to pollution events in the southeast of the UK. These sources must therefore all be well-characterised and constrained to understand air quality around London.

The relationship between indoor environment, outdoor environment, and behavior on indoor air quality and health

2021 ◽  
Author(s):  
SDAG Lab
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
The United States ◽  
Outdoor Environment ◽  
Equation Modeling ◽  
Health Symptoms ◽  
Surface Dust ◽  
Air Purifier ◽  
The Impact

We should be concerned about the impact of indoor air quality on health because in the United States, people spend most of their time indoors. While earlier studies have characterized the odds of developing illness based on the home environment, they have not investigated the behaviors that can ameliorate the negative effect of indoor, outdoor, and behavioral sources. The purpose of this study was to 1) investigate the contributions of indoor, outdoor, and behavioral sources of pollutants on health symptoms, and 2) to identify the behaviors that can worsen or mitigate the number of health symptoms. Data came from two surveys (n=83,284) and include questions on home conditions, outdoor conditions, occupants’ behaviors, and health symptoms. I used negative binomial regression and identified that demographics and outdoor characteristics explain 2% of the variability in health symptoms, and maintenance behaviors explain 8% of the variability in health symptoms. Next, structural equation modeling (SEM) was used to examine the behaviors that can mitigate or worsen the number of health symptoms. The results show that maintenance issue such as mold result in significantly more health symptoms (β = .12, p &lt;.001). and factors such as leaks, and frequent long shower may result in an increase in mold. Leaks may cause water stains (β = .39, p &lt;.001) which could lead to molds (β = .47, p &lt;.001). While frequent long shower can result in an increase in mold (β = .05, p &lt;.001), the use of a bathroom exhaust during shower may help to reduce molds (β = -.04, p &lt;.001). In terms of personal behaviors, the presence of carpet (β = .08, p &lt;.001), and smoking also result in an increase in surface dust (β = .17`, p &lt;.001) but frequent vacuuming could mitigate the impact of surface dust on health symptoms (β = -.12, p &lt;.001). Home occupants who live near environmental hazards are also likely to use air purifier (β = .03, p &lt;.001); however, air purifier is associated with more health symptoms (β = .05, p &lt;.001). Based on the findings, it is recommended that home occupants engage in periodic maintenance to prevent issues such as leaks from escalating to molds, regular vacuuming to reduce the accumulation of surface dust. Regarding air purifier, it could be that participants who experienced more health symptoms were more likely to use an air purifier. However, some air purifiers are sources of ozone, therefore home occupants should err on the side of caution when it comes to air purifier (Britigan et al., 2006; Cestonaro et al., 2017).

scholarly journals The impact of weather changes on air quality and health in the United States in 1994–2012

2015 ◽  
Vol 10 (8) ◽  
pp. 084009 ◽  
Author(s):  
Iny Jhun ◽  
Brent A Coull ◽  
Joel Schwartz ◽  
Bryan Hubbell ◽  
Petros Koutrakis
Keyword(s):  
United States ◽  
Air Quality ◽  
The United States ◽  
Weather Changes ◽  
The Impact

scholarly journals The impact of data assimilation on the prediction of Asian desert dust using an operational 4D-Var system

2018 ◽  
Author(s):  
Angela Benedetti ◽  
Francesca Di Giuseppe ◽  
Luke Jones ◽  
Vincent-Henri Peuch ◽  
Samuel Rémy ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Asian Dust ◽  
Added Value ◽  
Desert Dust ◽  
Deep Blue ◽  
Dust Events ◽  
The Impact

Abstract. Asian Dust is a seasonal meteorological phenomenon which affects East Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipation of their consequences is challenging. Three one-year experiments were run to assess the skill of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring Asian dust and understand its relative contribution to air quality over China. Data used were the MODIS Dark Target and the Deep Blue Aerosol Optical Depth. In particular the experiments aimed at understanding the added value of data assimilation runs over a model run without any aerosol data. The year 2013 was chosen as representative for the availability of independent Aerosol Optical Depth (AOD) data from two established ground-based networks (AERONET and CARSNET), which could be used to evaluate experiments. Particulate Matter (PM) data from the China Environmental Protection Agency (CEPA) were also used in the evaluation. Results show that the assimilation of satellite AOD data is beneficial to predict the extent and magnitude of desert-dust events and to improve the forecast of such events. The availability of observations from the MODIS Deep Blue algorithm over bright surfaces is an asset, allowing for a better localization of the sources and definition of the dust events. In general both experiments constrained by data assimilation perform better that the unconstrained experiment, generally showing smaller mean normalized bias and fractional gross error with respect to the independent verification datasets. The impact of the assimilated satellite observations is larger at analysis time, but lasts well into the forecast. While assimilation is not a substitute for model development and characterization of the emission sources, results indicate that it can play a big role in delivering improved forecasts of Asian Dust.

scholarly journals Variability of depolarization of aerosol particles in the megacity of Beijing: implications for the interaction between anthropogenic pollutants and mineral dust particles

2018 ◽  
Vol 18 (24) ◽  
pp. 18203-18217 ◽  
Author(s):  
Yu Tian ◽  
Xiaole Pan ◽  
Tomoaki Nishizawa ◽  
Hiroshi Kobayashi ◽  
Itsushi Uno ◽  
...  
Keyword(s):  
Air Quality ◽  
Mineral Dust ◽  
Aerosol Particles ◽  
Dust Particles ◽  
Urban Site ◽  
Anthropogenic Pollutants ◽  
Coarse Mode ◽  
Fine Mode ◽  
Dust Events ◽  
The Impact

Abstract. East Asia is suffering from severe air pollution problems due to intensive anthropogenic emissions and natural mineral dust aerosols. During transport, the aerosol particles undergo complex mixing processes, resulting in great impacts on regional air quality, human health and climate. In this study, we conducted a long-term observation using an optical particle counter equipped with a polarization detection module (POPC) at an urban site in Beijing. Mass concentrations of both PM2.5 and PM10 estimated from POPC compared well with ground-based measurements. The results revealed that the observed depolarization ratio (δ, termed as the ratio of the intensity of the s-polarized signal to the intensity of the 120∘ backward scattering signal [s/(s+p)]) for aerosol particles in the fine mode was generally much lower in summer than that in spring as a result of predominance of different aerosol types. Mineral dust particles in the coarse mode normally had a large δ value (0.3±0.05) owing to their nonspherical shape; however, particles in the fine mode mostly had water-soluble compositions, which led to an apparent decrease of their δ values in particular high relative humidity (RH) conditions. Because the observation site was subject to the impact of frequent dust events in spring, the δ value of particle at 1 µm was almost twice as high as that (0.07±0.01) in summer. Based on size-resolved δ values, anthropogenic pollutants, mineral dust and polluted mineral dust particles and their contribution to local air quality could be well distinguished. About 26.7 % of substandard days (daily averaged PM2.5 concentration larger than 75 µg m−3) in Beijing featured high atmospheric loading of coarse-mode particles in winter and springtime. In particular, during severe pollution episodes in winter, the δ values of coarse-mode particles decreased by 13 %, which implies a high possibility of dust-related heterogeneous processes in pollution formation. During dust events, δ values of particles with optical size (Dp) of 5 µm evidently decreased, with an increase of the PM2.5 ∕ PM10 ratio as well as RH, indicating the morphological changes of mineral dust. This study confirmed that high RH tends to promote water absorption processes on the dust surface as well as the coating of soluble compounds, and suggested that remote sensing techniques for aerosols may underestimate the impact of dust particles due to the complex mixing of dust and anthropogenic particles in urban areas, and the interaction between dust particles and pollutants should be considered well by the optical model.

scholarly journals The impact of stay-at-home orders on air-quality and COVID-19 mortality rate in the United States

Urban Climate ◽  
2021 ◽  
pp. 100946
Author(s):  
Samain Sabrin ◽  
Maryam Karimi ◽  
Rouzbeh Nazari ◽  
Md Golam Rabbani Fahad ◽  
Robert W. Peters ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Mortality Rate ◽  
The United States ◽  
The Impact ◽  
At Home

scholarly journals Satellite-based estimation of the impacts of summertime wildfires on PM<sub>2.5</sub> concentration in the United States

2021 ◽  
Vol 21 (14) ◽  
pp. 11243-11256
Author(s):  
Zhixin Xue ◽  
Pawan Gupta ◽  
Sundar Christopher
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Atmospheric Correction ◽  
Health Assessment ◽  
The United States ◽  
Ancillary Data ◽  
Leave One Out ◽  
The Impact

Abstract. Frequent and widespread wildfires in the northwestern United States and Canada have become the “new normal” during the Northern Hemisphere summer months, which significantly degrades particulate matter air quality in the United States. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellite-derived aerosol optical depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter concentration (PM2.5) air quality in the United States. We use a geographically weighted regression (GWR) method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate an overall leave-one-out cross-validation (LOOCV) R2 value of 0.797 with root mean square error (RMSE) between 3 and 5 µg m−3. Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year and that 15 of these states have PM2.5 concentrations more than 2 times that of the inactive year. Furthermore, these fires increased the daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 µg m−3, posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires, thereby providing useful information for various applications such as public health assessment.

scholarly journals Satellite-based Estimation of the Impacts of Summertime Wildfires on Particulate Matter Air Quality in United States

2020 ◽  
Author(s):  
Zhixin Xue ◽  
Pawan Gupta ◽  
Sundar Christopher
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Atmospheric Correction ◽  
Health Assessment ◽  
The United States ◽  
Ancillary Data ◽  
Weather Forecasts ◽  
The Impact

Abstract. Frequent and widespread wildfires in North Western United States and Canada has become the new normal during the northern hemisphere summer months, which degrades particulate matter air quality in the United States significantly. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellite-derived Aerosol Optical Depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter air quality (PM2.5) in the United States. We use a Geographically Weighted Regression method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire active year and 15 of these states have PM2.5 concentrations more than 2 times than that of the inactive year. Furthermore, these fires increased daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 µgm−3 posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires thereby providing useful information for various applications including public health assessment.

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