Makoto Kelp

Makoto Kelp
Harvard University | Harvard · Department of Earth and Planetary Sciences

About

15
Publications
1,423
Reads
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94
Citations
Additional affiliations
August 2018 - present
Harvard University
Position
  • PhD Student
June 2016 - August 2018
University of Washington Seattle
Position
  • Research Assistant
Education
August 2018 - May 2023
Harvard University
Field of study
  • Atmospheric Chemistry
August 2012 - May 2016
Reed College
Field of study
  • Chemistry

Publications

Publications (15)
Article
Full-text available
A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine‐learned (ML) solvers can offer order of magnitude speedup relative to conventional implicit solvers but past implementations have suffered from fast error growth and only...
Article
Full-text available
Considerable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior research on best sensor placement for monitoring fine particulate matter (PM 2.5 ) pollution is scarce: most stu...
Preprint
Full-text available
Considerable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior research on best sensor placement for monitoring fine particulate matter (PM2.5) pollution is scarce: most studi...
Preprint
Full-text available
A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine-learned (ML) solvers can offer order-of-magnitude speedup relative to conventional implicit solvers, but past implementations have suffered from fast error growth and only...
Article
Full-text available
Atmospheric chemistry models—components in models that simulate air pollution and climate change—are computationally expensive. Previous studies have shown that machine‐learned atmospheric chemical solvers can be orders of magnitude faster than traditional integration methods but tend to suffer from numerical instability. Here, we present a modelin...
Preprint
Atmospheric chemistry models—used as components in models that simulate air pollution and climate change—are computationally expensive. Previous studies have shown that machine-learned atmospheric chemical solvers can be orders of magnitude faster than traditional integration methods but tend to suffer from numerical instability. Here, we present a...
Article
The absolute principal component scores (APCS) model was applied to on-road, background-adjusted measurements of NOx, CO, CO2, black carbon (BC), and particle number (PN) obtained from a continuously moving platform deployed during 16 afternoon sampling periods in Los Angeles, CA. High-emitter biasing observations were separated from the vehicle fl...
Article
Full-text available
An important component of air quality engineering is quantifying in-use, fleet-average emission factors, and the spatial patterns of vehicle emissions. We report here that an absolute principal component score (APCS) analysis of on-road mobile measurements is a straightforward, efficient method for identifying the major contributors of traffic-rela...
Preprint
Full-text available
Chemical transport models (CTMs), which simulate air pollution transport, transformation, and removal, are computationally expensive, largely because of the computational intensity of the chemical mechanisms: systems of coupled differential equations representing atmospheric chemistry. Here we investigate the potential for machine learning to repro...
Article
Full-text available
Biomass combustion in residential cookstoves is a major source of air pollution and a large contributor to the global burden of disease. Carbon financing offers a potential funding source for health-relevant energy technologies in low-income countries. We conducted a randomized intervention study to evaluate air pollution impacts of a carbon-financ...
Article
Acetone is one of the most abundant carbonyl compounds in the atmosphere, and it serves as an important source of HOx (OH + HO2) radicals in the upper troposphere and a precursor for peroxyacetyl nitrate (PAN). We present a global sensitivity analysis targeted at several major natural source and sink terms in the global acetone budget to find the i...
Article
We examined the emissions of diesel particulate matter (DPM) and coal dust from trains in the Columbia River Gorge (CRG) in Washington State by measuring PM1, PM2.5, CO2, and black carbon (BC) during the summer of 2014. We also used video cameras to identify the train type and speed. During the two-month period, we identified 293 freight trains and...

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Projects

Project (1)
Project
To establish high-resolution vehicle emission inventories by using Intelligence Traffic System (ITS) traffic big data and various data-driven methods.