Infrared Photography as an Air Pollution Surveillance Instrument

Remote sensing is an extremely new science which developed from World War II technology. At that time, infrared sensitive film (false color) was used to detect such things as troop movements and camouflaged war materials. In essence, the film displayed a color contrast between the artificial and organic vegetation.     

Controlled Exposures of Volunteers to Respirable Carbon and Sulf uric Acid Aerosols

Respirable carbon or fly ash particles are suspected to increase the respiratory toxicity of coexisting acidic air pollutants, by concentrating acid on their surfaces and so delivering it efficiently to the lower respiratory tract. To investigate this issue, we exposed 15 healthy and 15 asthmatic volunteers in a controlled- environment chamber (21°C, 50 percent relative humidity) to four test atmospheres: (i) clean air; (ii) 0.5-μm H2SO4 aerosol at =100 μg/m³, generated from water solution; (iii) 0,5-μm carbon aerosol at =250 μg/m³, generated from highly pure carbon black with specific surface area comparable to ambient pollution particles; and (iv) carbon as in (iii) plus =100 μg/m³ of ultrafine H2SO4 aerosol generated from fuming sulfuric acid. Electron microscopy showed that nearly all acid in (iv) became attached to carbon particle surfaces, and that most particles remained in the sub-μm size range. Exposures were performed double-blind, 1 week apart. They lasted 1 hr each, with alternate 10-min periods of heavy exercise (ventilation =50 L/min) and rest. Subjects gargled citrus juice before exposure to suppress airway ammonia. Lung function and symptoms were measured pre-exposure, after initial exercise, and at endexposure. Bronchial reactivity to methacholine was measured after exposure. Statistical analyses tested for effects of H₂SO₄ or carbon, separate or interactive, on health measures. Group data showed no more than small equivocal effects of any exposure on any health measure. One individual's responses were consistent with a clinically significant excess airway constriction from H₂SO₄ plus carbon, and 2-3 others showed slight excess responses to the combined pollutants, but all these observations might have reflected chance variations. We conclude that coexisting carbon aerosol did not increase respiratory irritancy of H₂SO₄, in most healthy and asthmatic subjects exposed for 1 hr under simulated "worst-case" ambient conditions.     

Forecasting Air Pollution Potential: A Synoptic Climatological Approach

ABSTRACT

This paper describes the development and application of an air pollution potential (APP) forecast model based on a synoptic climatological approach in a heavily industrialized area in Durban, South Africa. The aim of the forecasting procedure, based on a system of orange, red, and all-clear alerts, was to give industry advance warning of periods of poor atmospheric dispersion so that it could take action to reduce emissions. The key meteorological parameter in accurately identifying the commencement of an APP episode was found to be negative surface pressure tendency. Wind direction was the most useful parameter in estimating the end point of an APP episode. The model was very successful in identifying periods of elevated SO₂, but there is a need for further refinement in forecasting the end point of an episode.     

Black Carbon Aerosol at McMurdo Station,Antarctica

ABSTRACT

Aerosol light absorption as black carbon (BC) was measured from November 19, 1995, to February 6, 1996, at a location 0.65 km downwind of the center of McMurdo Station on the Antarctic coast. The results show a bimo-dal frequency distribution of BC concentrations. Approximately 65% of the measurements were found in a mode at a low range of concentrations centered at ~20 ng/m³. These concentrations are higher than those found at other remote Antarctic locations and probably represent contamination from the station. The remaining measurements were in a high-concentration mode (BC ~300 ng/m³), indicating direct impact of local emissions from combustion activities at the station. High values of BC were associated with winds from the direction of the station, and the BC flux showed a clear directionality. Maximum BC concentrations occurred between 7:00 and 11:00 a.m. The "polluted" mode accounted for more than 80% of the BC frequency-weighted impact at this location.     

Partitioning of metals in a degraded acid sulfate soil landscape: influence of tidal re-inundation

The oxidation and acidification of sulfidic soil materials results in the re-partitioning of metals, generally to more mobile forms. In this study, we examine the partitioning of Fe, Cr, Cu, Mn, Ni and Zn in the acidified surface soil (0-0.1 m) and the unoxidised sub-soil materials (1.3-1.5 m) of an acid sulfate soil landscape. Metal partitioning at this acidic site was then compared to an adjacent site that was previously acidified, but has since been remediated by tidal re-inundation. Differences in metal partitioning were determined using an optimised six-step sequential extraction procedure which targets the “labile”, “acid-soluble”, “organic”, “crystalline oxide”, “pyritic” and “residual” fractions. The surficial soil materials of the acidic site had experienced considerable losses of Cr, Cu, Mn and Ni compared to the underlying parent material due to oxidation and acidification, yet only minor losses of Fe and Zn. In general, the metals most depleted from the acidified surface soil materials exhibited the greatest sequestration in the surface soil materials of the tidally remediated site. An exception to this was iron, which accumulated to highly elevated concentrations in the surficial soil materials of the tidally remediated site. The “acid-soluble”, “organic” and “pyritic” fractions displayed the greatest increase in metals following tidal remediation. This study demonstrates that prolonged tidal re-inundation of severely acidified acid sulfate soil landscapes leads to the immobilisation of trace metals through the surficial accumulation of iron oxides, organic material and pyrite.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.