Topic
Air pollutant concentrations
About: Air pollutant concentrations is a research topic. Over the lifetime, 1652 publications have been published within this topic receiving 36138 citations.
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TL;DR: Wang et al. as discussed by the authors developed a land use regression model using regulatory monitoring data to predict the spatial distribution of air pollutant concentrations in Jinan, China, where traffic, land use and census data, and meteorological and physical conditions were included as candidate independent variables, and were tabulated for buffers of varying radii.
Abstract: SO2, NO2, and PM10 are the major outdoor air pollutants in China, and most of the cities in China have regulatory monitoring sites for these three air pollutants. In this study, we developed a land use regression (LUR) model using regulatory monitoring data to predict the spatial distribution of air pollutant concentrations in Jinan, China. Traffic, land use and census data, and meteorological and physical conditions were included as candidate independent variables, and were tabulated for buffers of varying radii. SO2, NO2, and PM10 concentrations were most highly correlated with the area of industrial land within a buffer of 0.5 km (R2=0.34), the distance from an expressway (R2=0.45), and the area of residential land within a buffer of 1.5 km (R2=0.25), respectively. Three multiple linear regression (MLR) equations were established based on the most significant variables (p<0.05) for SO2, NO2, and PM10, and R2 values obtained were 0.617, 0.640, and 0.600, respectively. An LUR model can be applied to an area with complex terrain. The buffer radii of independent variables for SO2, NO2, and PM10 were chosen to be 0.5, 2, and 1.5 km, respectively based on univariate models. Intercepts of MLR equations can reflect the background concentrations in a certain area, but in this study the intercept values seemed to be higher than background concentrations. Most of the cities in China have a network of regulatory monitoring sites. However, the number of sites has been limited by the level of financial support available. The results of this study could be helpful in promoting the application of LUR models for monitoring pollutants in Chinese cities.
32 citations
TL;DR: In this article, the authors examined the concentration changes in air pollutants (i, carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matters (PM25 and PM10) during the period March-April 2020 data from both satellite observations (for NO2) and ground-based measurements (for all other pollutants) were utilized to analyze the changes when compared against the same months between 2015 and 2019 Globally, space borne NO2 column observations observed by satellite (OMI on Aura) were reduced by approximately 9
32 citations
08 Jul 2014
TL;DR: In this article, the authors set national air quality standards for six common air pollutants and analyzed the results of their analyses to this web site and posted the results to the web site.
Abstract: EPA sets national air quality standards for six common air pollutants. Each year EPA tracks the levels of these air pollutants in the air. EPA posts the results of our analyses to this web site.
32 citations
01 Jan 2014
TL;DR: Air pollution and greenhouse gases as discussed by the authors, air pollution, greenhouse gases, and air pollution and water pollution:, کتابخانه دیجیتال جندی اهواز
Abstract: Air pollution and greenhouse gases : , Air pollution and greenhouse gases : , کتابخانه دیجیتال جندی شاپور اهواز
31 citations
TL;DR: In this paper, a grid-based air quality model of the urban background with a plume-in-grid representation of roadway emissions is presented to simulate near-roadway concentrations due to emissions from a busy interstate highway in New York City.
Abstract: Several air toxics are emitted from mobile sources on roadways and these emissions account for a significant fraction of the health risks to the population. In addition, health effect studies are now becoming more comprehensive and some account for the spatial heterogeneities of air pollutant concentration fields (as is the case near roadways). Standard models can simulate either the near-source concentration fields or the urban background, but no model can handle both spatial scales in the vicinity of roadways in a coherent and scientifically correct manner. Here, we present a model that provides such an integrated treatment by combining a grid-based air quality model of the urban background with a plume-in-grid representation of roadway emissions. The model is applied to simulate near-roadway concentrations due to emissions from a busy interstate highway in New York City. Qualitative comparisons with typical measured concentration profiles show that the model captures the observed features of toxic air pollutant concentrations near roadways.
31 citations