Related Experiment Video
Updated: Feb 1, 2026
08:59
An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice
Published on: March 3, 2023
2.8K
Spatial PM2.5 mobile source impacts using a calibrated indicator method
Xinxin Zhai1, James A Mulholland1, Mariel D Friberg1
1a School of Civil and Environmental Engineering , Georgia Institute of Technology , Atlanta , GA, USA.
Journal of the Air & Waste Management Association (1995)
|December 1, 2018
Summary
This study enhances methods to estimate fine particulate matter (PM2.5) from vehicles, improving health impact assessments. The new approach provides detailed spatial and temporal data on mobile source pollution.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Public Health
Background:
- Motor vehicles are significant sources of fine particulate matter (PM2.5), linked to adverse health outcomes.
- Traditional receptor models for source impact assessment are constrained by limited observational data.
- Accurate spatiotemporal estimation of mobile source impacts on PM2.5 is crucial for health studies.
Purpose of the Study:
- To develop an enhanced approach for estimating temporally and spatially resolved mobile source impacts on PM2.5.
- To improve upon the integrated mobile source indicator (IMSI) method using updated data and calibration techniques.
- To provide reliable data for investigating the health effects of traffic pollution.
Main Methods:
- Extended the integrated mobile source indicator (IMSI) method.
- Generated spatially resolved indicators using fused Community Multiscale Air Quality (CMAQ) model simulations and observations for elemental carbon (EC), carbon monoxide (CO), and nitrogen oxide (NOx) at 4 km resolution.
- Utilized spatially resolved emissions and spatially calibrated unitless indicators with Chemical Mass Balance (CMB) model results for daily mobile source impact estimation.
Main Results:
- Estimated daily total mobile source impacts on PM2.5, and separate gasoline and diesel vehicle impacts, at 12 km and 4 km resolutions for Georgia.
- Demonstrated high temporal correlations (R = 0.59–0.88) between estimated mobile source impacts and daily CMB results.
- Found that total mobile source impacts showed higher correlation and lower error compared to separate gasoline and diesel source impacts against observation-based CMB estimates.
Conclusions:
- The enhanced approach provides accurate, spatially resolved mobile source impacts comparable to observation-based estimates.
- This method effectively estimates daily mobile source impacts on PM2.5 using readily available air pollutant data and modeling.
- The improved estimates are suitable for health effect assessments related to traffic pollution.
Related Concept Videos
02:39Indicators
60.7K
Certain organic substances change color in dilute solution when the hydronium ion concentration reaches a particular value. For example, phenolphthalein is a colorless substance in any aqueous solution with a hydronium ion concentration greater than 5.0 × 10−9 M (pH < 8.3). In more basic solutions where the hydronium ion concentration is less than 5.0 × 10−9 M (pH > 8.3), it is red or pink. Substances such as phenolphthalein, which can be used to determine the pH of a solution, are...
60.7K
01:11Glassware Calibration
1.4K
Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
1.4K
01:12Instrument Calibration
755
Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
755
01:18Methods of Documentation I: Source-Oriented Records
1.7K
Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
In an SOR, each discipline involved in patient care maintains a separate medical record section. This record-keeping method enables easy tracking of patient progress and ensures healthcare staff have access to up-to-date information.
Key Attributes include the following:
In an SOR, each discipline involved in patient care maintains a separate medical record section. This record-keeping method enables easy tracking of patient progress and ensures healthcare staff have access to up-to-date information.
Key Attributes include the following:
1.7K
01:19Impact of Groups on Groups
247
Social psychologists analyze how groups influence one another, shaping social structures and interactions through both cooperation and competition. These dynamics manifest in various ways, ranging from economic partnerships to intergroup conflicts that shape societal structures and perceptions.Cooperation and Competition in Intergroup RelationsIntergroup relationships vary across contexts, sometimes fostering cooperation and mutual benefit while at other times leading to conflict and...
247
01:10Calibration Curves: Correlation Coefficient
4.9K
In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
4.9K