scholarly journals 2012 Multivariate air pollutant exposure prediction in South Carolina

2018 ◽  
Vol 2 (S1) ◽  
pp. 21-21
Author(s):  
Ray Boaz ◽  
Andrew Lawson ◽  
John Pearce
Keyword(s):  
South Carolina ◽  
Goodness Of Fit ◽  
Predictive Accuracy ◽  
Quality Measurement ◽  
Air Pollutant ◽  
Data Availability ◽  
Chemical Components ◽  
Monitoring Networks ◽  
Criteria Air Pollutants ◽  
Pollutant Concentrations

OBJECTIVES/SPECIFIC AIMS: The objective of this project is the application of complex fusion models, which combine observed and modeled data, to areas with sparse monitoring networks with multiple chemical components is under-developed. Such models could provide improved accuracy and coverage for air quality measurement predictions, an area greatly limited by the amount of missing data. METHODS/STUDY POPULATION: This project focuses on the development of methods for improved estimation of pollutant concentrations when only sparse monitor networks are found. Sparse monitoring networks are defined as areas where fewer than three criteria air pollutants (based on EPA standards) are monitored. Particularly, a multivariate air pollutant statistical model to predict spatio-temporally resolved concentration fields for multiple pollutants simultaneously is developed and evaluated. The multivariate predictions allow monitored pollutants to inform the prediction of nonmonitored pollutants in sparse networks. RESULTS/ANTICIPATED RESULTS: Daily, ZIP code level pollutant concentration estimates will be provided for 8 pollutants across South Carolina, and goodness of fit metrics for model variants and previously established methods will be compared. DISCUSSION/SIGNIFICANCE OF IMPACT: These methods utilize only widely available data resources, meaning that the improved predictive accuracy of sparsely monitored pollutant concentrations can benefit future studies in any US area by improving estimation of health effects and saving resources needed for supplemental air pollutant monitoring campaigns. Our method for estimation attempts to improve predictive accuracy and data availability for sparsely monitored pollutants and areas.

scholarly journals Evaluation of Land Use Regression Models for Nitrogen Dioxide and Benzene in Four US Cities

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Shaibal Mukerjee ◽  
Luther Smith ◽  
Lucas Neas ◽  
Gary Norris
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
El Paso ◽  
Passive Samplers ◽  
Data Availability ◽  
Border Crossings ◽  
Monitoring Networks ◽  
Land Use Regression ◽  
Pollutant Concentrations

Spatial analysis studies have included the application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks in El Paso and Dallas, TX, Detroit, MI, and Cleveland, OH to assess spatial variability and source influences. LURs were successfully developed to estimate pollutant concentrations throughout the study areas. Comparisons of development and predictive capabilities of LURs from these four cities are presented to address this issue of uniform application of LURs across study areas. Traffic and other urban variables were important predictors in the LURs although city-specific influences (such as border crossings) were also important. In addition, transferability of variables or LURs from one city to another may be problematic due to intercity differences and data availability or comparability. Thus, developing common predictors in future LURs may be difficult.

scholarly journals Long-term behavior and stability of calibration models for NO and NO<sub>2</sub> low cost sensors

2022 ◽  
Author(s):  
Horim Kim ◽  
Michael Müller ◽  
Stephan Henne ◽  
Christoph Hüglin
Keyword(s):  
Electrochemical Sensors ◽  
Low Cost ◽  
Air Pollutant ◽  
Coefficient Of Determination ◽  
Monitoring Networks ◽  
Pollution Levels ◽  
Pollutant Concentrations ◽  
Air Quality Measurements ◽  
One Year

Abstract. Low-cost sensors are considered as exhibiting great potential to complement classical air quality measurements in existing monitoring networks. However, the use of low-cost sensors poses some challenges. In this study, the behavior and performance of electrochemical sensors for NO and NO2 were determined over a longer operating period in a real-world deployment. After careful calibration of the sensors, based on co-location with reference instruments at a rural traffic site during six months and by using robust linear regression and random forest regression, the coefficient of determination of both types of sensors were high (R2 > 0.9) and the root mean square error (RMSE) of NO and NO2 sensors were about 6.8 ppb and 3.5 ppb, respectively, for 10-minute mean concentrations. The RMSE of the NO2 sensors, however, more than doubled, when the sensors were deployed without re-calibration for a one-year period at other site types (including urban background locations), where the range and the variability of air pollutant concentrations differed from the calibration site. This indicates a significant effect of the re-location of the sensors on the quality of their data. During deployment, we found that the NO2 sensors are capable of distinguishing general pollution levels, but they proved unsuitable for accurate measurements, mainly due to significant biases. In order to investigate the long-term stability of the original calibration, the sensors were re-installed at the calibration site after deployment. Surprisingly, the coefficient of determination and the RMSE of the NO sensor remained almost unchanged after more than one year of operation. In contrast, the performance of the NO2 sensors clearly deteriorated as indicated by a higher RMSE (about 7.5 ppb, 10-minute mean concentrations) and a lower coefficient of determination (R2 = 0.59).

scholarly journals The causal effects of chronic air pollution on the intensity of COVID-19 disease: Some answers are blowing in the wind

2021 ◽  
Author(s):  
Marc N Conte ◽  
Matthew Gordon ◽  
Nicole Swartwood ◽  
Rachel Wilwerding ◽  
Chu A. (Alex) Yu
Keyword(s):  
New York ◽  
Ambient Air ◽  
Air Pollutant ◽  
Pollution Monitoring ◽  
Causal Relationships ◽  
Monitoring Networks ◽  
Pollutant Concentrations ◽  
Potential Benefits ◽  
Clean Air ◽  
Air Pollutant Concentrations

The threats posed by COVID-19 have catalyzed a search by researchers across multiple disciplines for policy-relevant findings about critical risk factors. We contribute to this effort by providing causal estimates of the link between increased chronic ambient pollutant concentrations and the intensity of COVID-19 disease, as measured by deaths and hospitalizations in New York City from March through August, 2020. Given concerns about unobservable characteristics that contribute to both ambient air pollutant concentrations and the impacts of COVID-19 disease, we instrument for pollutant concentrations using the time spent downwind of nearby highways and estimate key causal relationships using two-stage least squares models. The causal links between increases in concentrations of our traffic-related air pollutants (PM2.5, NO2, and NO) and COVID-19 deaths are much larger than the correlations presented in recent observational studies. We find that a 0.16 μg/m3 increase in average ambient PM2.5 concentration leads to an approximate 30% increase in COVID-19 deaths. This is the change in concentration associated with being downwind of a nearby highway. We see that this effect is mostly driven by residents with at least 75 years of age. In addition to emphasizing the importance of searching for causal relationships, our analysis highlights the value of increasing the density of pollution-monitoring networks and suggests potential benefits of further tightening of Clean Air Act amendments, as our estimated effects occur at concentrations well below thresholds set by the National Ambient Air Quality Standards.

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 Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals Evolution of Gaseous and Particulate Pollutants in the Air: What Changed after Five Lockdown Weeks at a Southwest Atlantic European Region (Northwest of Spain) Due to the SARS-CoV-2 Pandemic?

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 562
Author(s):  
Jorge Moreda-Piñeiro ◽  
Joel Sánchez-Piñero ◽  
María Fernández-Amado ◽  
Paula Costa-Tomé ◽  
Nuria Gallego-Fernández ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Traffic ◽  
Statistical Significance ◽  
Temporal Trends ◽  
Air Pollutant ◽  
Concentration Data ◽  
Southwest Atlantic ◽  
Pollutant Concentrations ◽  
Air Quality Monitoring Stations ◽  
Almost All

Due to the exponential growth of the SARS-CoV-2 pandemic in Spain (2020), the Spanish Government adopted lockdown measures as mitigating strategies to reduce the spread of the pandemic from 14 March. In this paper, we report the results of the change in air quality at two Atlantic Coastal European cities (Northwest Spain) during five lockdown weeks. The temporal evolution of gaseous (nitrogen oxides, comprising NOx, NO, and NO2; sulfur dioxide, SO2; carbon monoxide, CO; and ozone, O3) and particulate matter (PM10; PM2.5; and equivalent black carbon, eBC) pollutants were recorded before (7 February to 13 March 2020) and during the first five lockdown weeks (14 March to 20 April 2020) at seven air quality monitoring stations (urban background, traffic, and industrial) in the cities of A Coruña and Vigo. The influences of the backward trajectories and meteorological parameters on air pollutant concentrations were considered during the studied period. The temporal trends indicate that the concentrations of almost all species steadily decreased during the lockdown period with statistical significance, with respect to the pre-lockdown period. In this context, great reductions were observed for pollutants related mainly to fossil fuel combustion, road traffic, and shipping emissions (−38 to −78% for NO, −22 to −69% for NO2, −26 to −75% for NOx, −3 to −77% for SO2, −21% for CO, −25 to −49% for PM10, −10 to −38% for PM2.5, and −29 to −51% for eBC). Conversely, O3 concentrations increased from +5 to +16%. Finally, pollutant concentration data for 14 March to 20 April of 2020 were compared with those of the previous two years. The results show that the overall air pollutants levels were higher during 2018–2019 than during the lockdown period.

scholarly journals Exposure to chemical components of fine particulate matter and ozone, and placenta-mediated pregnancy complications in Tokyo: a register-based study

2021 ◽  
Author(s):  
Takehiro Michikawa ◽  
Seiichi Morokuma ◽  
Shin Yamazaki ◽  
Akinori Takami ◽  
Seiji Sugata ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Organic Carbon ◽  
Pregnancy Complications ◽  
Fine Particulate Matter ◽  
First Trimester ◽  
Chemical Components ◽  
Specific Chemical ◽  
Network Database ◽  
Fine Particulate ◽  
Pollutant Concentrations

Abstract Background Maternal exposure to fine particulate matter (PM2.5) was associated with pregnancy complications. However, we still lack comprehensive evidence regarding which specific chemical components of PM2.5 are more harmful for maternal and foetal health. Objective We focused on exposure over the first trimester (0–13 weeks of gestation), which includes the early placentation period, and investigated whether PM2.5 and its components were associated with placenta-mediated pregnancy complications (combined outcome of small for gestational age, preeclampsia, placental abruption, and stillbirth). Methods From 2013 to 2015, we obtained information, from the Japan Perinatal Registry Network database, on 83,454 women who delivered singleton infants within 23 Tokyo wards (≈627 km2). Using daily filter sampling of PM2.5 at one monitoring location, we analysed carbon and ion components, and assigned the first trimester average of the respective pollutant concentrations to each woman. Results The ORs of placenta-mediated pregnancy complications were 1.14 (95% CI = 1.08–1.22) per 0.51 μg/m3 (interquartile range) increase of organic carbon and 1.11 (1.03–1.18) per 0.06 μg/m3 increase of sodium. Organic carbon was also associated with four individual complications. There was no association between ozone and outcome. Significance There were specific components of PM2.5 that have adverse effects on maternal and foetal health.

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