Performance evaluation of exhaust aftertreatment devices used for emissions control on diesel engines employed in underground coal mines

This study was initiated to assist the WV Diesel Equipment Commission in its promulgation of initial rules, requirements, and standards governing the operation of diesel-powered equipment in underground coal mines. Four different engines and various exhaust after treatment devices that represent current levels of in-use technology were selected for performance evaluation. Both eddy-current and water-brake dynamometers were used to load the engines according to an ISO 8-Mode test cycle. Experimental emissions data, sampled from a full-flow dilution tunnel, suggests that particulate traps can reduce the mass emission rates of particulate matter (DPM) by nearly 90%, while reductions in fuel sulfur content (0.04% compared to 0.37% by mass) can reduce DPM mass emissions by as much as 22%. The study concluded that the singular usage of catalytic converters is not recommended for the confined spaces of a mining environment, due to their tendency to enhance particulate matter sulfate production and possibly increase overall exhaust toxicity

Oceanic Lidar

Instrument concepts which measure ocean temperature, chlorophyll, sediment and Gelbstoffe concentrations in three dimensions on a quantitative, quasi-synoptic basis were considered. Coastal zone color scanner chlorophyll imagery, laser stimulated Raman temperaure and fluorescence spectroscopy, existing airborne Lidar and laser fluorosensing instruments, and their accuracies in quantifying concentrations of chlorophyll, suspended sediments and Gelbstoffe are presented. Lidar applications to phytoplankton dynamics and photochemistry, Lidar radiative transfer and signal interpretation, and Lidar technology are discussed

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm

AVIRIS calibration using the cloud-shadow method

More than 90 percent of the signal at an ocean-viewing, satellite sensor is due to the atmosphere, so a 5 percent sensor-calibration error viewing a target that contributes but 10 percent of the signal received at the sensor may result in a target-reflectance error of more than 50 percent. Since prelaunch calibration accuracies of 5 percent are typical of space-sensor requirements, recalibration of the sensor using ground-base methods is required for low-signal target. Known target reflectance or water-leaving radiance spectra and atmospheric correction parameters are required. In this article we describe an atmospheric-correction method that uses cloud shadowed pixels in combination with pixels in a neighborhood region of similar optical properties to remove atmospheric effects from ocean scenes. These neighboring pixels can then be used as known reflectance targets for validation of the sensor calibration and atmospheric correction. The method uses the difference between water-leaving radiance values for these two regions. This allows nearly identical optical contributions to the two signals (e.g., path radiance and Fresnel-reflected skylight) to be removed, leaving mostly solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by incident solar irradiance reaching the sea surface provides the remote-sensing reflectance of the ocean at the location of the neighbor region

Satellite-Sensor Calibration Verification Using the Cloud-Shadow Method

An atmospheric-correction method which uses cloud-shaded pixels together with pixels in a neighboring region of similar optical properties is described. This cloud-shadow method uses the difference between the total radiance values observed at the sensor for these two regions, thus removing the nearly identical atmospheric radiance contributions to the two signals (e.g. path radiance and Fresnel-reflected skylight). What remains is largely due to solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by the direct solar irradiance reaching the sea surface and correction for some second-order effects provides the remote-sensing reflectance of the ocean at the location of the neighbor region, providing a known 'ground target' spectrum for use in testing the calibration of the sensor. A similar approach may be useful for land targets if horizontal homogeneity of scene reflectance exists about the shadow. Monte Carlo calculations have been used to correct for adjacency effects and to estimate the differences in the skylight reaching the shadowed and neighbor pixels

Evaluation of Heavy- and Medium-Duty On-Road Vehicle Emissions in California\u27s South Coast Air Basin

Emission measurements were collected from heavy-duty (HDVs) and medium-duty vehicles (MDVs) at the Peralta weigh station long-term measurement site near Anaheim, CA in 2017. Two Fuel Efficiency Automobile Test units sampled elevated and ground-level exhaust vehicles totaling 2,315 measurements. HDVs (1844 measurements) exhibited historical reductions in fuel specific oxides of nitrogen (NOx) from the 2008 measurements (55%) with increased use of exhaust gas recirculation and selective catalytic reduction systems. However, as these technologies have aged, the in-use benefits have declined. Infrared %opacity measurements of tailpipe soot decreased 14% since 2012 with increased diesel particulate filter (DPF) use, DPF longevity and fleet turnover. 63% of the HDV fleet in 2017 was chassis model year 2011+ compared to only 12% in 2012. The observed MDV fleet (471 measurements) was 1.4 years older than the HDV fleet with average NOx 14% higher. A significant reduction in MDV NOx occurred approximately 2 model years prior to similar HDV reductions (2014 versus 2016 chassis model year). MDV chassis model years 2014+ were able to meet their corresponding NOx laboratory certification standards in-use, whereas HDVs remain slightly above this threshold. Similar MDV NOx emission trends were also observed in data previously collected in Chicago, IL

Thermophysical optimization of specialized concrete pavement materials for collection of surface heat energy and applications for shallow heat storage

There is great potential to use pavement structures to collect and/or store solar energy for the heating and cooling of adjacent buildings, e.g. airport terminals, shopping malls, etc. Therefore, pavement materials comprising both conventional and unconventional concrete mixtures with a wide range of densities, thermal conductivities, specific heat capacities, and thermal diffusivities were investigated. Their thermo-physical properties were then used as inputs to a one dimensional transient heat transport model in order to evaluate the temperature changes at the various depths at which heat might be abstracted or stored. The results indicated that a high diffusivity pavement, e.g. incorporating high conductive aggregates and/or metallic fibres, can significantly enhance heat transfer as well as reduction of thermal stresses across the concrete slab. On the other hand a low diffusivity concrete can induce a more stable temperature at shallower depth enabling easier heat storage in the pavement as well as helping to reduce the risk of damage due to freeze-thaw cycling in cold regions

Overprescribing of potentially harmful medication: an observational study in England’s general practice

Background: Overprescribing of potentially harmful medication in UK general practice has a complex association with socioeconomic deprivation. Aim: To assess trends in general practice prescribing of five high-risk medications and their relationship with deprivation. Design & setting: An observational study was conducted using general practice data from three English regions with varied sociodemographic factors: West Yorkshire and Harrogate (WY), Black Country and West Birmingham (BC), and Surrey and East Sussex (SE). Method: Practice-level prescribing data were obtained from 2016–2021 for five drug classes: opioids, hypnotics, gabapentinoids, non-steroidal anti-inflammatory drugs (NSAIDs), and antibacterials. Prescribing trends were demonstrated using a linear model. Results: Reduction in NSAID, opioid, hypnotic and antibacterial prescriptions, and the increase in gabapentinoid prescriptions, were significant at each financial year time period. Index of Multiple Deprivation (IMD) was positively associated with all drug classes except antibacterials, which showed a positive association when incorporating the interaction term between IMD and age. When adjusting for IMD and population, region was independently associated with prescribing rate. Compared with WY, IMD had a smaller association with prescribing in BC for NSAIDs (coefficient = −0.01578, P = 0.004) and antibacterials (coefficient = −0.02769, P = 0.007), whereas IMD had a greater association with prescribing in SE for NSAIDs (coefficient = 0.02443, P<0.001), opioids (coefficient = 0.08919, P<0.001), hypnotics (coefficient = 0.09038, P<0.001), gabapentinoids (coefficient = 0.1095, P<0.001), and antibacterials (coefficient = 0.01601, P = 0.19). Conclusion: The association of socioeconomic deprivation with overprescribing of high-risk medication in general practice varies by region and drug type. Geographical location is associated with overprescribing, independent of socioeconomic status

Estimating primary production at depth from remote sensing

By use of a common primary-production model and identical photosynthetic parameters, four different methods were used to calculate quanta 1Q2 and primary production 1P2 at depth for a study of high-latitude North Atlantic waters. The differences among the four methods relate to the use of pigment information in the upper water column. Methods 1 and 2 use pigment biomass 1B2 as an input and a subtropical, empirical relation between K d 1diffuse attenuation coefficient2 and B to estimate Q at depth. Method 1 uses measured B, but Method 2 uses B derived from the Coastal Zone Color Scanner 1subtropical algorithm2 as inputs. Methods 3 and 4 use the phytoplankton absorption coefficient 1a ph 2 instead of B as input, and Method 3 uses empirically derived a ph 14402 and K d values, and Method 4 uses analytically derived a ph 14402 and a 1total absorption coefficient2 values based on the same remote measurements as Method 2. When the calculated and the measured values of Q1z2 and P1z2 were compared, Method 4 provided the closest results 3for P1z2, r 2 5 0.95 1n 5 242, and for Q1z2, r 2 5 0.92 1n 5 1124. Method 1 yielded the worst results 3for P1z2, r 2 5 0.56 and for Q1z2, r 2 5 0.814. These results indicate that one of the greatest uncertainties in the remote estimation of P can come from a potential mismatch of the pigment-specific absorption coefficient 1a ph *2, which is needed implicitly in current models or algorithms based on B. We point out that this potential mismatch can be avoided if we arrange the models or algorithms so that they are based on the pigment absorption coefficient 1a ph 2. Thus, except for the accuracy of the photosynthetic parameters and the above-surface light intensity, the accuracy of the remote estimation of P depends on how accurately a ph can be estimated, but not how accurately B can be estimated. Also, methods to derive a ph empirically and analytically from remotely sensed data are introduced. Curiously, combined application of subtropical algorithms for both B and K d to subarctic waters apparently compensates to some extent for effects that are due to their similar and implicit pigment-specific absorption coefficients for the calculation of Q1z2