Source attribution of volatile organic compounds (VOCs) can be challenging in urban areas, which have many point sources. Mobile laboratories using time-of-flight mass spectrometers (TOF-MS) can take measurements throughout areas of concern, resulting in data with high spatial resolution that can be used to more easily identify these sources. However, emissions in heavily polluted areas still undergo significant mixing over short distances, making source attribution of some compounds challenging. Positive matrix factorization (PMF) has been widely used for attributing pollutants to different sources when taking stationary measurements due to its ability to process large amounts of data into generally interpretable results. However, some limitations of PMF can impact its usefulness to mobile data; PMF is a computationally intensive process, requires some user choices in attributing factors to emissions sources, and results can be significantly impacted by chemical transformations after emission. Here, both PMF and a simpler comparative analysis method are evaluated in analyzing measurements taken in the Elyria Swansea neighborhood of Commerce City, CO. This neighborhood is located near an oil refinery, a wastewater treatment plant, local industrial shops, and major highways. PMF failed to differentiate between oil refinery emissions and traffic emissions, and had difficulties recognizing other key sources. A simpler comparative analysis showed that the refinery contributed significantly to VOC concentrations throughout the neighborhood, including air toxics such as benzene. A wastewater treatment plant contributed to methanethiol and dimethyl sulfide. Finally, a small woodshop was identified as a hyperlocal VOC source, and contributed high amounts of some VOCs, such as toluene and other solvents, in its immediate surroundings.: This work discusses mobile measurements of VOCs around Commerce City, CO, a heavily polluted urban area north of Denver, using a PTR-TOF-MS. Two different source attribution methods, positive matrix factorization (PMF) and comparative analysis, were evaluated in the context of mobile measurements. The results show that an oil refinery and a woodshop contributed greatly to many VOC concentrations in the Elyria Swansea residential area of Commerce City. Additional sources, such as a wastewater treatment plant, also contributed to some odorous VOCs. PMF was unable to fully describe sources based on the mobile data. Comparative analysis was useful in attributing more VOCs to different sources, but quantitative results were influenced by how the analysis is set up. These findings are relevant to the residents of Denver and regulatory bodies to better understand Denver air pollution, as well as to other mobile studies doing source attribution of VOCs.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/10962247.2024.2379927 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
School of Management, Tianjin University of Commerce, Tianjin, 300134, China.
Decoupling economic growth and carbon emissions is essential to a sustainable high-quality development. As a small unit of the engine of development, more research has begun to focus on city-level issues. In order to fill the gaps in the decoupling research at the city level covering the whole nationwide, this paper applied the bottom-up method to calculate 282 cities' carbon emissions according to China's city-level panel data of terminal energy consumption, and combined Tapio decoupling with LMDI decomposition model to analyze cities' decoupling status and its driving factors.
View Article and Find Full Text PDFFront Public Health
January 2025
Innovation Center of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, West China School of Nursing, Sichuan University, Chengdu, Sichuan, China.
Introduction: The residential environment significantly impacts the mental health of older adults. Urban agglomeration planning, while fostering regional economic development, also influences the psychological well-being of this demographic.
Methods: This study investigates the effects of urban agglomeration planning on depression levels in older adults, utilizing cohort data from the China Health and Retirement Longitudinal Study (CHARLS) and the multi-temporal double-difference-in-differences (DID) model.
PLoS One
December 2024
Department of Health Promotion, Education and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States of America.
Introduction: Several Indian states have banned the sale of loose cigarettes, and India is considering a national ban. This study examines the perceptions of policymakers, implementers, and law enforcement officials regarding the implementation and enforcement of this ban.
Methods: Between May-October 2022, we conducted in-depth interviews with 26 key stakeholders involved in tobacco control in two Indian cities, Delhi (where the ban was not implemented) and Mumbai (where the ban was in effect).
PLoS One
December 2024
School of Systems Engineering, Kochi University of Technology, Kami, Kochi, Japan.
This study conducts a comprehensive analysis of gender inequality in Sri Lanka, focusing on the relationship between key socioeconomic factors and the Gender Inequality Index (GII) from 1990 to 2022. By applying machine learning techniques, including Decision Trees and Ensemble methods, the study investigates the influence of economic indicators such as GDP per capita, government expenditure, government revenue, and unemployment rates on gender disparities. The analysis reveals that higher GDP and government revenues are associated with reduced gender inequality, while greater unemployment rates exacerbate disparities.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Rail Transportation, Soochow University, Suzhou 215131, China; Intelligent Urban Rail Engineering Research Center of Jiangsu Province, Suzhou 215131, China. Electronic address:
The field of traffic forecasting has been the subject of considerable attention as a critical component in alleviating traffic congestion and improving urban services. Given the regular patterns of human activities, it is evident that traffic flow is inherently periodic. However, most of existing studies restrict themselves to recent historical observations and typically yield structurally and computationally complex models, which greatly limits the forecasting accuracy and hinders the application of models in realistic situations.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!