Derivation and Use of Simple Relationships between Aerodynamic and Optical Particle Measurements

Moore, Kori D.; Martin, Randal S.; Bradford, W. J.; Marchant, Christian C.; Jones, Deb; Wojcik, Michael D.; Pfeiffer, Richard; Prueger, John H.; Hatfield, Jerry L.

doi:10.1061/(asce)ee.1943-7870.0000893

Cited by 2 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In past field campaigns, MCF 2.5 has generally been higher than MCF 10 and MCF TSP values, but these MCF 2.5 values were much higher than those seen before and account for the majority of values above 5 g · cm −3 reported in Ref. 21. Due to the nonphysically large numbers, the calculated MCF 2.5 was not used.…”

Section: Particulate-matter Concentration Measurementsmentioning

confidence: 92%

“…While several studies have found that PM 2.5 and PM 10 levels reported by MiniVols are very similar to concentrations measured by federal reference method (FRM, see 40 CFR 50.6 and 50.7) monitors, the slope of the particle removal Dependent on calibration and environmental conditions efficiency versus particle size curve of the MiniVol impactor assembly is less steep than required by FRM samplers. [18][19][20][21] Therefore, PM levels reported by the MiniVols should be considered as close approximations to those that would be given by FRM samplers.…”

Section: Instrumentation and Sample Layoutmentioning

confidence: 99%

“…These data were used to calculate mass conversion factors (MCFs) for each size fraction (k), as described in detail by Ref. 21. In summary, the MCF k is calculated using PM k reported by MiniVols and V k , averaged over the MiniVol sample time, from each sample location through the following equation:…”

Section: Instrumentation and Sample Layoutmentioning

confidence: 99%

See 2 more Smart Citations

Particulate-matter emission estimates from agricultural spring-tillage operations using LIDAR and inverse modeling

Moore

Wojcik

Martin

et al. 2015

J. Appl. Remote Sens

Self Cite

View full text Add to dashboard Cite

Abstract. Particulate-matter (PM) emissions from a typical spring agricultural tillage sequence and a strip-till conservation tillage sequence in California's San Joaquin Valley were estimated to calculate the emissions control efficiency (η) of the strip-till conservation management practice (CMP). Filter-based PM samplers, PM-calibrated optical particle counters (OPCs), and a PM-calibrated light detection and ranging (LIDAR) system were used to monitored upwind and downwind PM concentrations during May and June 2008. Emission rates were estimated through inverse modeling coupled with the filter and OPC measurements and through applying a mass balance to the PM concentrations derived from LIDAR data. Sampling irregularities and errors prevented the estimation of emissions from 42% of the sample periods based on filter samples. OPC and LIDAR datasets were sufficiently complete to estimate emissions and the strip-till CMP η, which were ∼90% for all size fractions in both datasets. Tillage time was also reduced by 84%. Calculated emissions for some operations were within the range of values found in published studies, while other estimates were significantly higher than literature values. The results demonstrate that both PM emissions and tillage time may be reduced by an order of magnitude through the use of a strip-till conservation tillage CMP when compared to spring tillage activities.

show abstract

Section: Particulate-matter Concentration Measurementsmentioning

confidence: 92%

Section: Instrumentation and Sample Layoutmentioning

confidence: 99%