Matthew Landis

Dr. Matthew Landis

orcid

Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 February 2002 in Environmental Science & Technology
Verified
Journal Article
Closed access
SLSteve E. Lindberg
Steve E. Lindberg
SBSteve Brooks
Steve Brooks
Che-Jen LinChe-Jen Lin
Che-Jen Lin
KSKaren J. Scott
Karen J. Scott
MLMatthew Landis
Matthew Landis
ARAndreas Richter
Andreas Richter

24 May 2002 in Environmental Science & Technology
Verified
Journal Article
Closed access
MLMatthew Landis
Matthew Landis
RSRobert K. Stevens
Robert K. Stevens
FSFrank Schaedlich
Frank Schaedlich
EPEric M. Prestbo
Eric M. Prestbo

22 August 2018 in Atmospheric Measurement Techniques
Verified
Journal Article
Open access
PDF file
Tongshu ZhengTongshu Zheng
Tongshu Zheng
MBMichael H. Bergin
Michael H. Bergin
Karoline K. BarkjohnKaroline K. Barkjohn
Karoline K. Barkjohn
STSachchida N Tripathi
Sachchida N Tripathi
SSShilpa Shirodkar
Shilpa Shirodkar
DCDavid E. Carlson
David E. Carlson
Low-cost particulate matter (PM) sensors are promising tools for supplementing existing air quality monitoring networks. However, the performance of the new generation of low-cost PM sensors under field conditions is not well understood. In this study, we characterized the performance capabilities of a new low-cost PM sensor model (Plantower model PMS3003) for measuring PM2.5 at 1 min, 1 h, 6 h, 12 h, and 24 h integration times. We tested the PMS3003 sensors in both low-concentration suburban regions (Durham and Research Triangle Park (RTP), NC, US) with 1 h PM2.5 (mean ± SD) of 9±9 and 10±3 µg m−3, respectively, and a high-concentration urban location (Kanpur, India) with 1 h PM2.5 of 36±17 and 116±57 µg m−3 during monsoon and post-monsoon seasons, respectively. In Durham and Kanpur, the sensors were compared to a research-grade instrument (environmental β attenuation monitor, E-BAM) to determine how these sensors perform across a range of PM2.5 concentrations and meteorological factors (e.g., temperature and relative humidity, RH). In RTP, the sensors were compared to three Federal Equivalent Methods (FEMs) including two Teledyne model T640s and a Thermo Scientific model 5030 SHARP to demonstrate the importance of the type of reference monitor selected for sensor calibration. The decrease in 1 h mean errors of the calibrated sensors using univariate linear models from Durham (201 %) to Kanpur monsoon (46 %) and post-monsoon (35 %) seasons showed that PMS3003 performance generally improved as ambient PM2.5 increased. The precision of reference instruments (T640: ±0.5 µg m−3 for 1 h; SHARP: ±2 µg m−3 for 24 h, better than the E-BAM) is critical in evaluating sensor performance, and β-attenuation-based monitors may not be ideal for testing PM sensors at low concentrations, as underscored by (1) the less dramatic error reduction over averaging times in RTP against optically based T640 (from 27 % for 1 h to 9 % for 24 h) than in Durham (from 201 % to 15 %); (2) the lower errors in RTP than the Kanpur post-monsoon season (from 35 % to 11 %); and (3) the higher T640–PMS3003 correlations (R2 ≥ 0.63) than SHARP–PMS3003 (R2 ≥ 0.25). A major RH influence was found in RTP (1 h RH = 64±22 %) due to the relatively high precision of the T640 measurements that can explain up to ∼ 30 % of the variance in 1 min to 6 h PMS3003 PM2.5 measurements. When proper RH corrections are made by empirical nonlinear equations after using a more precise reference method to calibrate the sensors, our work suggests that the PMS3003 sensors can measure PM2.5 concentrations within ∼ 10 % of ambient values. We observed that PMS3003 sensors appeared to exhibit a nonlinear response when ambient PM2.5 exceeded ∼ 125 µg m−3 and found that the quadratic fit is more appropriate than the univariate linear model to capture this nonlinearity and can further reduce errors by up to 11 %. Our results have substantial implications for how variability in ambient PM2.5 concentrations, reference monitor types, and meteorological factors can affect PMS3003 performance characterization.

16 January 2018 in Environmental Health Perspectives
Verified
Journal Article
Open access
YKYong Ho Kim
Yong Ho Kim
SWSarah H. Warren
Sarah H. Warren
QKQ. Todd Krantz
Q. Todd Krantz
CKCharly King
Charly King
RJRichard Jaskot
Richard Jaskot
MGM. Ian Gilmour
M. Ian Gilmour
A peer-reviewed open access journal published by the National Institute of Environmental Health Sciences

23 September 2016 in Atmospheric Chemistry and Physics
Verified
Journal Article
Open access
PDF file
FSFrancesca Sprovieri
Francesca Sprovieri
NPNicola Pirrone
Nicola Pirrone
MBMariantonia Bencardino
Mariantonia Bencardino
Francesco D'AmoreFrancesco D'Amore
Francesco D'Amore
FCFrancesco Carbone
Francesco Carbone
CNClaus Norstrom
Claus Norstrom
Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS) project was funded by the European Commission (http://www.gmos.eu) and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010–2015), analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

8 October 2002 in Environmental Science & Technology
Verified
Journal Article
Closed access
MLMatthew Landis
Matthew Landis
GKGerald J. Keeler
Gerald J. Keeler