CleAir monitoring system for particulate matter. A case in the Napoleonic Museum in Rome

Monitoring the air particulate concentration both outdoors and indoors is becoming a more relevant issue in the past few decades. An innovative, fully automatic, monitoring system called CleAir is presented. Such a system wants to go beyond the traditional technique (gravimetric analysis), allowing for a double monitoring approach: the traditional gravimetric analysis as well as the optical spectroscopic analysis of the scattering on the same filters in steady-state conditions. The experimental data are interpreted in terms of light percolation through highly scattering matter by means of the stretched exponential evolution. CleAir has been applied to investigate the daily distribution of particulate matter within the Napoleonic Museum in Rome as a test case

Controlling Ozone and Fine Particulates: Cost Benefit Analysis with Meteorological Variability

In this paper, we develop an integrated cost-benefit analysis framework for ozone and fine particulate control, accounting for variability and uncertainty. The framework includes air quality simulation, sensitivity analysis, stochastic multi-objective air quality management, and stochastic cost-benefit analysis. This paper has two major contributions. The first is the development of stochastic source-receptor (S-R) coefficient matrices for ozone and fine particulate matter using an advanced air quality simulation model (URM-1ATM) and an efficient sensitivity algorithm (DDM-3D). The second is a demonstration of this framework for alternative ozone and PM2.5 reduction policies. Alternative objectives of the stochastic air quality management model include optimization of the net social benefits and maximization of the reliability of satisfying certain air quality goals. We also examine the effect of accounting for distributional concerns.ambient air, ozone, particulate matter, risk management, public policy, cost-benefit analysis, variability and uncertainty, stochastic simulation, stochastic multi-objective programming, decisionmaking, National Ambient Air Quality Standards

Source-Receptor Relationships for Ozone and Fine Particulates in the Eastern United States

A key question in developing effective mitigation strategies for ozone and particulate matter is identifying which source regions contribute to concentrations in receptor regions. Using a direct approach with a regional, multiscale three-dimensional model, we derive multiple source-receptor matrices (S-Rs) to show inter- and intrastate impacts of emissions on both ozone and PM2.5 over the eastern United States. Our results show that local (in-state) emissions generally account for about 23% of both local ozone concentrations and PM2.5 concentrations, while neighboring states contribute much of the rest. The relative impact of each state on others varies dramatically between episodes. In reducing fine particulate concentrations, we find that reducing SO2 emissions can be 10 times as effective as reducing NOx emissions. SO2 reductions can lead to some increase in nitrates, but this is relatively small. NOx reductions, however, lead to both ozone reductions and some reduction in nitrate and sulfate particulate matter.source-receptor, ozone, particulate matter, sensitivity analysis, air quality simulation, National Ambient Air Quality Standards

Does Air Quality Matter? Evidence from the Housing Market

This study exploits the quasi-random assignment of air pollution changes across counties induced by federally mandated air pollution regulations to identify the impact of particulate matter on property values. Two striking empirical regularities emerge from the analysis. First particulate matter declined substantially more in regulated than in unregulated counties during the 1970s and 1980s. At the same time, housing prices rose more in regulated counties. The evidence suggests that this approach identifies two causal effects: 1) the impact of regulation on air quality improvements, and 2) the impact of regulation on economic gains for home-owners. In addition, the results highlight the importance of choosing regulatory instruments that are orthogonal to unobserved housing price shocks that vary by county over long time horizons. It appears that using regulation-induced changes in particulate matter leads to more reliable estimates of the capitalization of air quality into property values. Whereas the conventional cross-sectional and unstable and indeterminate across specifications, the instrumental variables estimates are much larger, insensitive to specification of the model, and appear to purge the biases in the conventional estimates. The estimates imply that a one-unit reduction in suspended particulates results in a 0.7-1.5 percent increase in home values. In addition, it appears that air pollution regulations resulted in real economic benefits to home-owners in regulated counties.

Complexity analysis in particulate matter measurements

We investigated the complex temporal fluctuations of particulate matter data recorded in London area by using the Fisher-Shannon (FS) information plane. In the FS plane the PM10 and PM2.5 data are aggregated in two different clusters, characterized by different degrees of order and organization. This results could be related to different sources of the particulate matter

Levels of heavy metals composition in atmospheric aerosol samples and the influence of african episodes

Particulate matter pollution is a serious environmental issue mainly due to the presence of toxic substances and trace metals in the atmosphere from a variety of pollution emission sources. Information about aerosol composition and their sources especially during pollution events can be further used to establish strategies for the reduction of particulate matter concentration. The objective in the present study was to analyse variations in total suspended particle (TSP) mass concentration and heavy metal components for evaluating the atmospheric loadings of substances with different sources as well as to further examine the relationship between the occurrence of African dust intrusions and metallic species concentrations at our coastal station located in South Spain. Non-destructive Wavelength-Dispersive X-Ray Fluorescence (WDXRF) analysis has been applied for the determination of multi-element contents of atmospheric particulate matter.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Life Support Filtration System Trade Study for Deep Space Missions

The National Aeronautics and Space Administrations (NASA) technical developments for highly reliable life support systems aim to maximize the viability of long duration deep space missions. Among the life support system functions, airborne particulate matter filtration is a significant driver of launch mass because of the large geometry required to provide adequate filtration performance and because of the number of replacement filters needed to a sustain a mission. A trade analysis incorporating various launch, operational and maintenance parameters was conducted to investigate the trade-offs between the various particulate matter filtration configurations. In addition to typical launch parameters such as mass, volume and power, the amount of crew time dedicated to system maintenance becomes an increasingly crucial factor for long duration missions. The trade analysis evaluated these parameters for conventional particulate matter filtration technologies and a new multi-stage particulate matter filtration system under development by NASAs Glenn Research Center. The multi-stage filtration system features modular components that allow for physical configuration flexibility. Specifically, the filtration system components can be configured in distributed, centralized, and hybrid physical layouts that can result in considerable mass savings compared to conventional particulate matter filtration technologies. The trade analysis results are presented and implications for future transit and surface missions are discussed

The effect of butanol isomers on the formation of carbon particulate matter in fuel-rich premixed ethylene flames

Abstract The effect of the butanol isomers on carbon particulate matter formation was studied by substituting up to 20% of the total carbon of ethylene, fed to premixed flames with different equivalence ratios, with the four butanol isomers. Soot and condensed-phase nanostructures were tracked by means of particle size distribution (PSD) measurements and laser induced emission spectroscopy, namely fluorescence and incandescence. Butanol isomers, especially t-butanol, significantly reduced the total amount and the size of the soot particles, whereas a negligible effect was detected on condensed-phase nanostructures. PSDs were measured along with the aromaticity and functionalities of the carbon particulate matter thermophoretically sampled in the highest equivalence ratio condition. No significant differences were found among the different butanol isomers neither in the soot aggregate size, as measured by size exclusion chromatography, nor in the aromaticity, as evaluated by Raman and UV–vis spectroscopy, of the particulate matter. Conversely, FTIR analysis showed that carbon particulate matter produced from 1-butanol and t-butanol-doped flames contained larger amounts of oxygen in form of C = O, C–O–C and OH functionalities. However, most of the differences in the oxygen functionalities disappeared after dichloromethane (DCM) treatment, suggesting that these oxygenated moieties belong to the condensed-phase nanostructures, soluble in DCM, rather than to soot particles