Suchergebnisse

Der Überblick über die Entwicklung des westeuropäischen Integrationsprozesses nach dem Zweiten Weltkrieg läßt Inkongruenz und unterschiedliche Intensität der Zielsetzungen der Beteiligten erkennen. Ein Durchbruch bei den Einigungsbemühungen gelang daher erst vor dem Hintergrund des Kalten Krieges und wegen der als notwendig erachteten Kontrolle des deutschen Wiederaufstiegs. Nach einem Attraktivitätsverlust des Integrationsprojektes (EGKS, EVG) wurden die Römischen Verträge zum politisch motivierten Versuch, die europäische Idee zu retten und ein politisches Europa über die Bündelung ökonomischer Interessen (Kernenergie, Agrarmarkt, Abbau von Handelshemmnissen) zu schaffen. Sie blieben offen im Blick auf das Endziel der Gemeinschaft. (AuD-Hng)

The oil and gas sector in Ethiopia, currently at a very early stage of development, shows good potential for development on the long-run. The sector will benefit from strategies and policies to implement the broader vision for the sector. Development of the oil and gas sector in Ethiopia has the potential to transform the country's economy. To this end, the Government of Ethiopia (GoE) has requested technical assistance and capacity building support from the World Bank as part of a wider package of support provided by the Bank (in coordination with other development partners) to develop the extractive industries (oil, gas, and mining) sector of Ethiopia. The main objective of the work to be undertaken, is to provide guidance and build capacity in GoE as it undertakes the wider update of its policy, legal, and regulatory framework of the oil and gas sector. Adam Smith International (ASI) was contracted to review the policy and regulatory framework for the oil and gas sector and provide recommendations. This final report on policy and regulatory options has been prepared at the conclusion of the analytical stage of the project, and was preceded by the initiation report submitted in July 2015. This report has two objectives. Firstly, to provide a comprehensive review of the current policy of the GoE towards the oil and natural gas sector. Secondly, to evaluate the regulatory framework in terms of good international practice.

The Country Partnership Framework (CPF) for Montene gro covers the period from July 1, 2015 to June 30, 2020 (fiscal years 2016-2020). This CPF builds on the results and lessons of the previous World Bank Group (WBG) Country Partnership Strategy (CPS), which originally covered the period July 1, 2011 to June 30, 2014, and was subsequently extended to June 30, 2015.The one-year CPS) extension was intended to provide greater clarity on the country's medium-term macro-fiscal framework as a basis for the new CPF, and to give additional time to make progress on improving environmental management, a key pillar of the CPS. The new CPF seeks to address the top priorities identified by the recently completed Systematic Country Diagnostic (SCD) as those that Montenegro needs to most urgently tackle to advance in its path towards shared prosperity and sustainable development. The CPF will selectively support Montenegro's development agenda outlined in the Montenegro Development Directions (MDD) 2015-2018, Economic Reform program (ERP) 2015-2017 and the Montenegro European Union (EU) Accession Program 2014-17. The WBG strategy will continue to support, and be aligned with, Montenegro's EU accession and integration process. The formulation of the new CPF benefitted from extensive consultations held in October 2015 and in January and March 2016, and involving several line ministries, municipalities, civil society, academia, and private sector across various regions of the country, as well as representatives of the international development community. The resulting proposal for engagement under the FY16-20 CPF reflects a broad consensus of a wide range of stakeholders and a shared understanding of development priorities and challenges facing the country.

This note lays out the rationale for including land administration quality index in the standard 'registering property' indicator by doing business and discusses initial evidence from the global sample, showing that many countries, including some that have performed well on Doing Business's traditional ranking, have a long way to go to establish a system of land administration that is reliable and transparent, achieves sufficient coverage, and minimizes disputes. The cases in this brochure document that by smartly deploying new technology, countries can make progress in this direction irrespective of their initial income level. Continued monitoring and learning from experience at all levels had an important role in facilitating such progress. Doing Business will contribute to this agenda by elevating the profile of land governance, tracking countries' performance with respect to land administration quality index, and fostering global exchange and learning from good performers.

In a recent survey of European economic growth since 1950, Crafts and Toniolo (2008) conclude that incentive structures are a crucial explanator of comparative growth rates of the economies of east and west Europe. Pre-empting that, a 2006 report on trade performance and policies in Eastern Europe and Central Asia included as one of its key recommendations the need to reduce the mean and variance of the tariff equivalents of trade barriers, and in particular to reduce unilaterally the policy regimes' anti-export bias, especially in countries exporting primary products (Broadman 2006). To progress such reform in Europe's transition economies efficiently and effectively, and to see how recent policies line up with those of the European Union (EU), requires better information on the extent of reform during the past two decades and of current policy influences on incentives within and between sectors. Immediately prior to their transition to market economies, policies in the region greatly distorted producer and consumer incentives, especially for agricultural products. Those distortions have been reduced substantially in several countries, but large variations remain across the region and distortions appear to be growing again in some countries. Now is thus an opportune time to examine how policies affecting agriculture are evolving in this region, including as part of the adjustment to EU accession for ten of the transition economies in the region.

Remember when the Fed's most pressing policy concern was missing their 2% inflation target from below for most of the decade following the financial crisis of 2008-09?  The concern never failed to puzzle me in all my time at the St. Louis Fed. I once let out how I really felt:All those years I was expecting low inflation and low interest rates to make the political opposition to ever-higher deficits melt away. As I recall explaining to my colleagues at the time "Either we'll get the biggest free-lunch of all time (increased government spending and/or tax cuts) or we'll get inflation." The inflation was inevitable, to my of thinking. I just didn't know when it would return. I certainly did not see the point of encouraging it! Well, inflation returned. But not exactly for the reasons I was expecting. What happened? ShocksWhat happened was COVID-19 and the Russia-Ukraine war. These two shocks were large, disruptive, and persistent. A great many people died. Large parts of the economy were shut down with the hope of slowing the spread of the virus so as not to overwhelm our limited ICU capacity. The leisure and hospitality sector was crushed, and other sectors as well. There was a massive (and highly unusual) reallocation of production and consumption away from services to goods--a phenomenon that has not fully reversed to this day. We learned about the delicate and interconnected nature of global supply chains. People modified their behavior in dramatic ways. Work-from-home seems here to stay. And then, of course, as if a global pandemic was not enough, Russia invaded Ukraine in early 2022, leading to the usual sickening consequences of war: death, destruction, and displacement--as well as energy disruptions and food shortages that reverberated across the global economy. This is not, of course, the only thing that happened. We also had policy responses. Policy: What was neededI want to limit attention to economic policy here (health policy is another matter). The COVID-19 shock disrupted some sectors of the economy more than others. Some sectors, like leisure and hospitality were virtually shut down. But in many other parts of the economy, people were able to work from home. Since not many people purchased pandemic-insurance, a large number of Americans were in for a whole lot of economic hurt. Most of those adversely affected were in the bottom half of the income distribution. What could and should have been done?I should like to think that most Americans would have been in favor of a social insurance program that supported those most in need; i.e., targeted transfers for as long as the pandemic remained disruptive. Most people would have recognized that this is the right thing to do. And even those few who seemingly do not care much for their fellow Americans might have recognized how redistribution would have been desirable, perhaps even necessary, to maintain social cohesion. We should not have wanted a replay of what happened in the last crisis, where the financial sector was bailed out while American many households were largely left flailing in the foreclosure winds that blew in the aftermath of 2008-09. How might such a program be financed? A consumption tax would have been one way. Imagine a "transitory" 5% federal sales tax to fund a targeted transfer program. The program parameters could, in principle, be calibrated in a manner that requires little or no adjustment in the deficit. Ideally, such an emergency program would have already been put in place. (As far as I know, there is still no such plan in place--a significant policy failure, in my view.)How might things have
played out with such a policy, given the sequence of shocks that unfolded? To a
first approximation, my guess is "probably not much different." With the balanced-budget
policy described above, inflation would have almost surely been lower. Imagine
shaving 300-500bp off the "inflation hump" we've experienced so far:

We would almost surely still have had some inflation stemming from supply disruptions and energy
costs (associated with the war). But inflation would have been less pronounced. Naturally, rather than complaining about high inflation, people would instead have
been complaining about high consumption taxes. ("They told us they'd be
transitory!") There's no such thing as a free lunch. 

Under this higher-tax/lower-deficit policy, most Americans would have felt worse off relative to
2019. The blame for this feeling, however, properly lies with the shocks and
not the policy response. Yes, work-from-home types would not have received
transfers and they would have been paying more for goods and services. This is
the nature of redistribution, which I believe most people would have supported. Policy: What we gotTo a large extent--and all things considered--we pretty much got what was needed: a set of redistributive policies with transfers targeted (mostly) to the bottom half of the income distribution (yes, yes, we can talk at length about how things could have been done better). Except that there was no surtax to fund the transfers. Our representatives in Congress chose to deficit-finance the programs. The resulting large quantity of treasury paper had to be absorbed by the private sector at a time supply was constrained and interest rates were not permitted to rise (I'll get to monetary policy in a moment). How does one not expect some additional inflation in this case? So, instead of a "transitory" consumption tax, we got a "transitory" inflation tax. There's no free lunch. By the way, by "transitory" I mean to say that inflation is expected to revert to target, instead of remaining elevated or even increasing. In the fall of 2020, I expected a "temporary" inflation (see here) because I thought the supply disruptions and CARES Act were not permanent. Inflation turned out to be higher and more persistent than I expected. But the supply disruptions have largely alleviated and the ARP expired at the end of 2021 (though the RUS-UKR war continues). Up until recently, I remained optimistic that--absent further shocks and with responsible fiscal policy--inflation would make its way back down to target in 3-5 years without a recession. I'm not as optimistic today, but let me return to this below. What about monetary policy? Well, I was very pleased with the way the Fed calmed financial markets in March 2020, as I expected it would.Well done, Fed. But what about monetary (interest rate) policy?Well, to be honest, monetary policy seemed a bit bonkers. Lowering the policy rate in response to recession engineered by a manufactured shutdown did not make much sense to me. My view was more in line with Michael Woodford's, as expressed here in his 2020 Jean Monnet lecture. What was needed was insurance, not stimulus. And this insurance needs to be delivered through fiscal policy. My own view is that many economists could not resist interpreting the severe decline in output as reflecting a conventional "output gap." To be fair, there may very well have been a decline in aggregate demand in the first half of 2020. The economic outlook at the time was very uncertain, which likely increased the desire for precautionary savings. Remember, monthly inflation rates for March, April and May of 2020 were negative. The monthly inflation rate only became positive in June 2020 (5.4% annualized rate), though it remained fairly subdued for most of  2020. Heading into 2020, the Fed's policy rate was around 1.6%. Was it really necessary to lower it any further? Especially in light of the fiscal transfers taking place throughout 2020?  But apparently, in the minds of some, perhaps even most, the economy needed "stimulating." In any case, it seems clear now, in retrospect at least, that the cut should probably not have happened or, conditional on happening, should have been quickly reversed once the financial panic had subsided. The main effect of interest rate policy according to many was an undesirable asset-price boom (stocks, bonds, and real estate). The increase in private sector wealth coming from higher asset valuations surely added some fuel to the inflationary fire.  We can now see how that Fed-induced wealth effect is being undone. The rapidity of the rise in the Fed's policy rate is wreaking havoc on wealth portfolios. This is not a huge concern to the extent the policy is just reversing an undesirable asset-price inflation. But to the extent that these assets sit on bank balance sheets, to the extent these positions are not hedged against duration risk, to the extent that depositors are skittish, and to the extent that capital buffers are running low, then the banking system--or at least parts of it--are subject to runs. We are seeing this play out now in the United States. Where are we heading? I fear we may be in a bit of a pickle. One reason is China. To be more precise, the risk of the U.S. entering a long and costly proxy war with China. Let's hope it doesn't happen. But I can't help thinking of Rome vs. Persia. I'm not sure about the Persian perspective, but my reading of history suggests that the late Roman Empire devoted considerable resources to defending its eastern frontier against its great rival. Such a fiscal strain requires taxes (or inflation).  If the Sino-American proxy war scenario fails to materialize, then I think we stand a reasonable chance of getting out of this decade without a recession, but with inflation hovering above target for the indefinite future. The Fed might want to sell this as part of its "symmetric" inflation targeting regime. After all, we tolerated undershooting the target inflation rate for a decade (see here). In my view, much will depend on the course of fiscal policy--the deficit, in particular--in relation to the global demand for U.S. Treasury securities (see here). Needless to say, these are very difficult objects to forecast. (In fact, there's no point in forecasting them -- we should just make contingency plans instead.)There is a chance that the Fed overdoes its policy tightening and starts to "break things." Given the recent events in the U.S. banking sector, the FOMC would, in my view, be wise to pause and see how things play out. This is not an issue of "financial dominance." It is based on the deflationary impulse induced by the recent bank failures. I expect all banks to redouble their efforts to repair their balance sheets. This means a fear-induced tightening of lending standards and slower loan growth beyond what one might consider to be a normal reaction against higher policy interest rates.  If the Fed does pull a Paul Volcker, then we'll get a sharp recession. Inflation will come down--temporarily, at least. Where inflation goes from there will depend, as always (in my view), on fiscal policy.  If the proxy war scenario does come to pass, then get ready to pay the necessary taxes. And remember: wars are typically inflationary. In fact, an inflation tax may not be a bad way to finance a part of this endeavor. The U.S. would effectively be collecting a greater amount of seigniorage on its U.S. Treasury securities held abroad. And why shouldn't our allies be prepared to shoulder some of the expense? (There are other ways, of course.) A proxy war may or may not be worth fighting. Either way, remember: there ain't no such thing as free lunch.  As for monetary policy in a period in which the government has a set objective and wants to deficit-finance its spending, I'm afraid the Fed will just have to learn how to stop worrying and "love" inflation (in case you're unfamiliar with the reference, see here). Raising interest rates sharply can break things and create disinflation. But without fiscal reform, the respite on inflation is likely to be temporary. In fact, inflation is likely to reemerge even higher than before since the Treasury will now have to issue paper at an even faster pace, first, to cover the shortfall created by the recession, and second, to cover the higher interest expense of the debt. This is a version of Sargent and  Wallace's "unpleasant monetarist arithmetic," see here and here. Need I add that creating a recession is no way to win a proxy war.  How will U.S. policy evolve to meet our many challenges? No one knows how the future will unfold. Perhaps we can take some comfort in Winston Churchill's observation: "You can always count on the Americans to do the right thing--but only after they've tried everything else." Alas, the quote is apocryphal. Nevertheless, I am hopeful that we will "do the right thing" eventually (and before it's too late). 

In the last decades digital modelling applied to geological research is getting increasing attention (Alaei, 2012; Tomassetti et al., 2018; Trippetta et al., 2020; De Franco et al., 2019; Mascolo and Lecomte, 2021). Indeed, relevant implications both in scientific and economic terms could be inferred by using this technique. In particular, the application of digital models in complex geologic scenarios is critical for the understanding of potentially exploitable systems from multiple perspectives. Starting from the most classical model application for the exploitation of oil and gas fields passing through the implementation of extraction strategies - by reducing uncertainties (Macgregor & Moody, 1998; Racey 2001) - digital models find new place in latest applications such as natural gas storage. Recently, models are also applied for the study of geological bodies, potential reservoirs for the CO2 or hydrogen injection (Dockrill and Shipton, 2010; Trippetta et al., 2013; Aminu et al., 2017; Heinemann et al., 2018). Modelling contribute and facilitate to capture and store gases in the subsurface, balancing their release into the atmosphere. Digital modelling represents one of the major innovative strategies in the control of greenhouse gases concentration in atmosphere, a currently trending topic from media, public opinion, and political points of view. Another possible application of digital models for subsurface gas storage involves the monitoring of reservoirs in order to ascertain and quantify gas leakage through fault or fracture systems (Wang et al., 2018). Moreover, radioactive waste storage could be integrated as current and powerful employment of digital models (Malvić et al., 2020). In particular, the technological tools used for these purposes are called forward models since their outcomes gives predictive results on the processes happened in the past and protracted towards the future. They appear extremely suitable for the study of geological subsurface formations that can be also applied to an emerging field such as the development of geothermal energy power plants (De Franco et al., 2019). All these are topics of great actuality since world governments' plans are1 directed towards the total replacement of classic energy sources from hydrocarbons with green energies. However, digital modelling needs input data such as geometries and rock properties that should be well constrained. Seismic exploration is probably the most powerful tool for investigating subsurface rock formations (Avseth et al., 2010). Important progress has been made in recent years, but significant problems remain in the geologic interpretation of seismic data. The reflections that can be read in seismic data depend on the Acoustic Impedance (AI) contrast in the transit of the P-wave between layers in the subsurface. AI depends on the density (ϼ) and the P-wave velocity (Vp) of the medium through which wave propagates (AI= ϼ Vp). These petrophysical characteristics, in turn, are controlled by structure, texture, porosity, and boundary conditions of the rocks (Dvorkin et al., 2014; Tomassetti et al., 2018; Trippetta et al., 2020; Brandano et al., 2020). These two links, one between rock structure and its elasticity and the other between elasticity and signal propagation, form the physical basis of seismic interpretation (Anselmetti and Eberli, 1993; Eberli et al. 2003; Weger et al. 2009; Hairabian et al. 2014; Dvorkin et al., 2014). Dealing with these relationships, we are facing the so- called inverse problem. We see from seismic sections the resulting seismic images of rock formations where the same signal can be the result of a combination of different features. It should be, thus, very useful to well understand what are the features that lead to a certain seismic image. Synthetic seismic modelling (or forward modelling) is a fundamental prospecting method for understanding the features leading to the corresponding seismic images of subsurface structures and reservoir architectures (Alaei, 2012). Forward modelling methodology, as approach to the interpretation of seismic data, involves the detailed characterization of lithology, density, porosity, seismic velocity and fluid in the rock, as well as the reservoir geometry. As a result, the corresponding seismic properties are calculated, and then synthetic seismic traces are generated. These issues became essential for lithologies characterized by a complex seismic interpretation (Al-Salmi et al., 2019). In addition, synthetic seismic forward models allow accurate analysis of fault zones. The study of seismic response in fault zones is crucial since the2 fracturing or compaction that faults create strongly modifies the petrophysical characteristics of rocks by affecting their properties (Botter et al., 2017; Kolyukhin et al., 2017). Synthetic seismic forward models are, therefore, mandatory for the comprehension of faults behaviour through seismic imaging. Faults play a key role in reservoirs by increasing or limiting fluid flow. Even if interpretation of seismic data is a pivotal method for studying the subsurface, the internal structure and properties of fault zones are often below the limit imposed by seismic resolution (Botter et al., 2017). Despite the impact of faults on reservoir permeability, modelling tools and workflows still lack for realistic representation of fault zones in models (Tveranger et al., 2005; Braathen et al., 2009; Manzocchi et al., 2010). With facies analysis and petrophysical data it is possible to build field-based digital models fundamental in understanding architectures of carbonate sedimentary bodies which often constitute reservoir surface analogues of buried world-wide petroleum systems, CO2, hydrogen, radioactive waste storage sites and geothermal fields. Surface analogues are rocks with depositional, textural, and petrophysical characteristics similar to those constituting the petroleum system, but they outcrop on the surface. Starting from petrophysical characteristics of facies, forward models can be built. In this thesis, as a case study for the development of a forward model, rocks belonging to the carbonate realm, more specifically carbonate ramps, were analyzed. Carbonate ramps constitute important hydrocarbon deposits in North Africa (Macgregor & Moody, 1998), Venezuela, and many other regions of the World (Racey, 2001) due to their excellent porosity and permeability characteristics. However, the depositional model that is the basis for a proper interpretation produces many uncertainties arising from the difficulty in attributing different facies to a depositional environment and process due to the poor occurrence of sedimentary structures (Buxton and Pedley, 1989; Pomar and Kendall, 2008; Burchette, 2012; Bassi et al., 2013; Tomassetti et al., 2018; Tomassetti et al., 2022). In addition, strong lateral heterogeneity in terms of petrophysical characteristics, components, structure, and texture leads to complex distinction of facies belts (Tomassetti et al., 2018; Trippetta et al., 2020; Brandano et al., 2020). To overcome these issues, quantification of3 petrophysical characteristics can be crucial in understanding facies heterogeneity from a physical perspective to be incorporated in synthetic seismic forward models building. Carbonate rocks are often difficult to interpret seismically because the slight acoustic impedance contrast at the interface between carbonate facies in subsurface does not allow a clear resolution of major reflectors and reservoir formations. Strong constraints are often imposed by geophysical survey techniques characterized by low resolution especially in carbonates and interpretation capabilities that depend on the interpreter skill (Tomassetti et al., 2018; Trippetta and Geremia, 2019; Faleide et al., 2021). These constraints can be overtaken through the modelling of surface analogues allowing a detailed analysis on the facies association but also their petrophysical characteristics and seismic properties such as acoustic impedance (Tomassetti et al., 2018; Lipparini et al., 2018; Trippetta and Geremia, 2019; Brandano et al., 2020). In order to analyse the petrophysical characteristics and seismic response of the carbonate realm through modelling two carbonate ramps both belonging to the Adria plate were considered as case studies. The first is the Chattian carbonate ramp of the Porto Badisco calcarenite outcropping in the southern Salento peninsula, the southernmost portion of the Apulian carbonate platform. The Porto Badisco carbonate ramp is an excellent surface analogue of exploited oil and gas field in the offshore Venezuela, Philippine and South China Sea (Zampetti et al., 2005; Sattler et al.,2004; Fournier and Borgomano, 2007; Lallier et al., 2012; Marini and Spadafora, 2014; Pomar et al., 2015; Valencia and Laya, 2020) as well as fields in offshore Adriatic Sea such as Ombrina Mare field (Campagnoni et al., 2013). In this carbonate system firstly the analysis of outcropping facies was carried out observing over 100 thin sections produced. Consequently facies association modelling was performed through Petrel software (mark of Schlumberger) using TGSim stochastic approach algorithm adopting the depositional model based on field data. This model is useful for qualitatively understand the broad facies spacial distribution which reflects the abrupt heterogeneity from a sedimentary point of view. To physically quantify the lateral facies heterogeneity the petrophysical characteristics such as porosity, density and seismic velocity were measured and analyzed through a multi-analytical approach. Density4 measurements were carried out with the helium pycnometer. Porosity was firstly calculated from the density data and then was additionally measured through image analysis and point counting to cross-correlate the values. Seismic velocity was measured by using an ultrasonic generator connected to piezoelectic transducers and to an oscilloscope. The analysis performed on the carbonate ramp outcropping in Porto Badisco offers the opportunity to analyze facies heterogeneity, modeling its distribution and physically quantifying it through petrophysical characterization. From the petrophysical data, it was possible to construct 2D models of the distribution of porosity and P-wave seismic velocity along the depositional model. This study, which can be applied globally to carbonate platforms, emphasizes with the modelling exercise how facies heterogeneity is an intrinsic feature of these systems. The petrophysical characterization which provides quantitative values to the heterogeneity allow to build more complex models such as seismic forward models discussed in the second chapter. The other case study is represented by the Cenozoic carbonate ramp outcropping on the Majella Massif in Abruzzi, the northernmost portion of the Apulian carbonate platform which gives the opportunity to study a carbonate ramp surface analogue of a buried reservoir. Also in Majella the Oligo- Miocene stratigraphic interval represented by the Bolognano Formation which is the reservoir of the system is considered an excellent surface analogue of the productive fields in the Adriatic Sea, offshore Venezuela, Philippines and many others worldwide (Tomassetti et al., 2021). Specifically, this system offers the opportunity to integrate the facies heterogeneity in the synthetic seismic forward modelling and understand its seismic response without the introduction of artificial noise to obtain additional information. On the Majella Massif a model of the facies heterogeneity to understand their seismic response was performed. After analyzing the facies and measuring their petrophysical characteristics, the data obtained were used as input for build a 3D property modelling in Petrel software representing the entire carbonate ramp from the topographic surface to the Upper Cretaceous from the platform top going towards the basin located northward from the Majella Massif. From the 3D model was cut a section whose data were used as input in Matlab (mark of Mathworks) in order to perform the synthetic seismic forward model5 with the geophysical codes provided by the CREWES consortium. The resulting forward model represent the seismic response of the facies heterogeneity of carbonate rocks. In addition, from the obtained seismic images it is possible to evaluate the presence of hydrocarbons and to identify how the presence of important bituminous impregnations – that can be appreciated in the field in Majella – modify the seismic response. The workflow developed to quantify the signature of the facies heterogeneity of carbonate rocks and the presence of infilling hydrocarbons is applicable to other systems worldwide, which is a large issue that is still open and can help in the problems relative to seismic interpretation associated with these systems. Given the presence of a buried normal fault system in the study area, a forward modelling in the fault zones was performed as well. By measuring the petrophysical characteristics of the fault rocks characterized by both fracturing or compaction, fault zones were modeled. Two end member scenarios with two opposite behaviors of the rocks belonging to the damage zone were modeled in Matlab. A scenario in which the damage zone is characterized by fracturing and therefore rocks affected by greater porosity than the host rock. In the other scenario was modeled a damage zone with lower porosity than the host rock caused by the presence of compaction bands. Consequently, the seismic response of these end members was compared to understand how faults affect the seismic response of carbonate ramp systems. Notoriously, fault systems globally characterize carbonate ramps, and understanding their seismic response facilitates interpretation of the deformation behavior that a fault can assume under different boundary conditions. This can lead to an understanding of whether faults behave as barriers or conduits for fluids with the important implications for the study of fluid leakage from reservoirs.

Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (Ntot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on Ntot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50g% and 60g% were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75g%) was required to document the diel cycle. Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (g1/4g102gcm-3) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day-night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (g1/4g103-104gcm-3) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate Ntot (g1/4g102-103gcm-3). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of Ntot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50gnm or >100gnm) can represent from a few percent to almost all of Ntot, corresponding to seasonal medians on the order of g1/4g10 to 1000gcm-3, with seasonal patterns and a hierarchy of the site types broadly similar to those observed for Ntot. Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol-cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate. ; NOAA base funding supports the observatories BRW, BND, MLO, SMO, SPO and THD, where efforts of the dedicated observatory staff and of programmer Derek Hageman are appreciated. BRW observations are also supported in part by the Atmospheric Radiation Measurement (ARM) user facility, a US Department of Energy (DOE) Office of Science user facility managed by the Biological and Environmental Research programme. Measurements at Welgegund are supported by North-West University, the University of Helsinki and the Finnish Meteorological Institute. This publication also forms part of the output of the Biogeochemistry Research Infrastructure Platform (BIOGRIP) of the Department of Science and Innovation of South Africa. Pallas and SMEAR II are grateful for the support of the Academy of Finland Centre of Excellence programme (project no. 272041), the Academy of Finland project Greenhouse gas, aerosol and albedo variations in the changing Arctic (project no. 269095), and the Novel Assessment of Black Carbon in the Eurasian Arctic: From Historical Concentrations and Sources to Future Climate Impacts (NABCEA, project no. 296302). Aerosol measurements at Anmyeon-do were supported by the Korea Meteorological Administration Research and Development Program "Development of Monitoring and Analysis Techniques for Atmospheric Composition in Korea" under grant KMA2018-00522. Measurements at Gosan were supported by the National Research Foundation of Korea (2017R1D1A1B06032548) and the Korea Meteorological Administration Research and Development Program under grant KMI2018-01111. The Lulin station is operated under the grants funded by the Taiwan Environmental Protection Administration. WLG is supported by the China Meteorological Administration, where efforts of the dedicated observatory staff are appreciated. Sites PDM, PUY, GIF, CHC and RUN are partially operated with the support of CNRS-INSU under the long-term observation programme and the French Ministry for Research under the ACTRIS-FR national research infrastructure. PDM and GIF received specific support from the French Ministry of the Environment. ATMO Occitanie is mentioned for sampling operations at PDM. Measurements at SIRTA are hosted by CNRS and by the alternative energies and atomic energy commission (CEA) with additional contributions from the French Ministry of the Environment through its funding to the reference laboratory for air quality monitoring (LCSQA). PUY is grateful for support from ATMO Auvergne Rhône Alpes for sampling operations and the support from the personnel of the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC). The specific support of the Institut de Recherche et Développement (IRD) in France and the Universidad Mayor de San Andrés in Bolivia support operations at CHC operations. The Steamboat Ski Resort provided logistical support and in-kind donations for SPL. The Desert Research Institute is a permittee of the Medicine Bow–Routt National Forests and an equal opportunity service provider and employer. SPL appreciates the extensive assistance of the NOAA/ESRL Federated Aerosol Network, of Ian McCubbin, site manager of SPL, and of Ty Atkins, Joe Messina, Dan Gilchrist and Maria Garcia, who provided technical assistance with the maintenance and data quality control for the aerosol instruments. SGP measurements/mentorship were supported by DOE-7F-30118 and staff on site. The Cape Grim Baseline Air Pollution Monitoring Station is grateful to the Australian Bureau of Meteorology for their long-term and continued support and all the staff from the Bureau of Meteorology and CSIRO, who have contributed to the generation of records reported here. The aerosol measurements at the Jungfraujoch were conducted with financial support from MeteoSwiss (GAW-CH aerosol monitoring programme) and from the European Union as well as the Swiss State Secretariat for Education, Research and Innovation (SERI) for the European Research Infrastructure for the observation of Aerosol, Clouds and Trace Gases (ACTRIS). The International Foundation High Altitude Research Station Jungfraujoch and Gornergrat (HFSJG) is mentioned for providing the research platform at the Jungfraujoch. The aerosol measurements at Kosetice received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109 and from the project for support of the national research infrastructure ACTRIS – participation of the Czech Republic (ACTRIS-CZ – LM2015037) supported by the Ministry of Education, Youth and Sports of CR within National Sustainability Program I (NPU I), grant agreement no. LO1415. The measurements were also supported by ERDF "ACTRIS-CZ RI" (no. CZ.02.1.01/0.0/0.0/16_013/0001315). Measurements at the Madrid site were funded by the following projects: CRISOL (CGL2017–85344-R MINECO/AEI/FEDER, UE), TIGAS-CM (Madrid Regional Government Y2018/EMT5177), AIRTEC-CM (Madrid Regional Government P2018/EMT4329), REDMAAS2020 (RED2018-102594-T CIENCIA) and Red de Excelencia ACTRIS-ESPAÑA (CGL2017-90884-REDT). Measurements at Montsec and Montseny were supported by the Spanish Ministry of Economy, Industry and Competitiveness and FEDER funds under project HOUSE (CGL2016-78594-R) and by the Generalitat de Catalunya (AGAUR 2017 SGR41 and the DGQA). Aerosol measurements at El Arenosillo Observatory are supported by the National Institute for Aerospace Technology and by different R&D projects of the Ministerio Español de Economía, Industria y Competitividad (MINECO). Aerosol measurements at UGR are supported by the Spanish Ministry of Economy and Competitiveness through projects no. CGL2016-81092-R, CGL2017-90884-REDT, RTI2018-097864-B-I00 and PGC2018-098770-B-I00 and by the Andalusia Regional Government through project no. P18-RT-3820. FKL, HAC and DEM are grateful for funding by project PANhellenic infrastructure for Atmospheric Composition and climate change (MIS 5021516), which is implemented under action Reinforcement of the Research and Innovation Infrastructure, funded by operational programme Competitiveness, Entrepreneurship and Innovation (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). CPC measurements at Sonnblick are supported by the Climate and Air Quality Commission of the Austrian Academy of Sciences and the office of the provincial government Salzburg, Unit 5/02. At CMN, aerosol measurements were partially supported by the Italian Ministry of Research and Education. Measurements at Birkenes II are financed by the Norwegian Environment Agency. VAV is grateful for various Swedish FORMAS, Swedish Research Council (VR) grants and the Magnus Bergvall and Märta och Erik Holmberg foundations and the Swedish EPA for making the research possible at the VAV site. NMY wishes to thank the many technicians and scientists of the Neumayer overwintering crews, whose outstanding commitment enabled continuous, high-quality aerosol records over many years. Gunter Löschau is acknowledged for his contribution to the data acquisition at ANB, DTC and DRN. Financial support This research was supported by the European Commission's Horizon 2020 Framework Programme (ACTRIS2 (grant agreement no. 654109)), the University of Helsinki, the Finnish Meteorological Institute, the Department of Science and Innovation of South Africa, the Academy of Finland Centre of Excellence programme (project no. 272041), the Academy of Finland project Greenhouse gas, aerosol and albedo variations in the changing Arctic (project no. 269095), the Novel Assessment of Black Carbon in the Eurasian Arctic: From Historical Concentrations and Sources to Future Climate Impacts (NABCEA, project no. 296302), the Korea Meteorological Administration Research and Development Program "Development of Monitoring and Analysis Techniques for Atmospheric Composition in Korea" (grant no. KMA2018-00522), the National Research Foundation of Korea (grant no. 2017R1D1A1B06032548), the Korea Meteorological Administration Research and Development Program (grant no. KMI2018-01111), the Taiwan Environmental Protection Administration, the China Meteorological Administration, the National Scientific Foundation of China (41675129, 41875147), the National Key R&D Program of the Ministry of Science and Technology of the People's Republic of China (grant no. 2016YFC0203305 and 2018YFC0213204), the Chinese Academy of Meteorological Sciences (2020KJ001), the Innovation Team for Haze-fog Observation and Forecasts of MOST and CMA, CNRS-INSU, the French Ministry for Research under the ACTRIS-FR national research infrastructure, the French Ministry of the Environment, MeteoSwiss (GAW-CH aerosol monitoring programme), the Swiss State Secretariat for Education, Research and Innovation (SERI), the Ministry of Education, Youth and Sports of CR within National Sustainability Program I (NPU I, grant no. LO1415), ERDF "ACTRISCZ RI" (grant no. CZ.02.1.01/0.0/0.0/16_013/0001315), CRISOL (CGL2017-85344-R MINECO/AEI/FEDER, UE), TIGAS-CM (Madrid Regional Government Y2018/EMT-5177), AIRTEC-CM (Madrid Regional Government P2018/EMT4329), REDMAAS2020 (RED2018-102594-T CIENCIA), Red de Excelencia ACTRIS-ESPAÑA (CGL2017-90884-REDT), the Spanish Ministry of Economy, Industry and Competitiveness, FEDER funds (project HOUSE, grant no. CGL2016-78594-R), the Generalitat de Catalunya (AGAUR 2017 SGR41 and the DGQA), the National Institute for Aerospace Technology, the Ministerio Español de Economía, Industria y Competitividad (MINECO), the Spanish Ministry of Economy and Competitiveness (projects no. CGL2016-81092-R, CGL2017-90884-REDT, RTI2018-097864-B-I00 and PGC2018-098770-B-I00), the Andalusia Regional Government (project no. P18-RT-3820), the PANhellenic infrastructure for Atmospheric Composition and climate change (MIS 5021516), Research and Innovation Infrastructure, Competitiveness, Entrepreneurship and Innovation (grant no. NSRF 2014-2020), the Italian Ministry of Research and Education, the Norwegian Environment Agency, Swedish FORMAS, the Swedish Research Council (VR), the Magnus Bergvall foundation, the Märta och Erik Holmberg foundation, and the Swedish EPA. ; Peer reviewed

학위논문(박사)--서울대학교 대학원 :보건대학원 환경보건학과,2020. 2. 윤충식. ; Ultrasonic humidifiers are commonly used in Korea because of cold and dry weather during winter and early spring, but there can be problems due to microbial growth in the humidifier reservoir. Humidifier disinfectants were widely used from 1994 to 2011 in Korea to prevent microbial contamination in ultrasonic humidifiers, but sales were then prohibited by the government following an outbreak of severe lung injury among humidifier disinfectant users. The main raw materials used for humidifier disinfectants were polyhexamethyleneguanidine (PHMG), oligo(2-(2-ethoxy)ethoxyethyl guanidine chloride (PGH), and methylchloroisothiazolinone/methylisothiazolinone (CMIT/MIT). Of these, PHMG phosphate (CAS No. 89697-78-9) was the most widely sold product, accounting for the overwhelming majority of fatalities. Therefore, this study aimed to identify the characteristics of PHMG in aqueous solution and investigate the behavior of airborne particles generated by the use of PHMG as a humidifier disinfectant; determine the difference in oligomer types and content between PHMG products and aerosols and estimate the airborne concentration of oligomers during humidifier use; and calculate the inhaled and deposited doses or fractions in the human lung using the ICRP and MPPD models for particles generated when a humidifier disinfectant containing PHMG was sprayed. First, three types of PHMG were selected (manufactured in Korea, USA, and China), with dynamic light scattering (DLS) used to determine their behavioral characteristics in aqueous solution. To determine the airborne behavioral characteristics, PHMG was diluted to obtain high (62.5–65 ppm) and low (6.25–6.5 ppm) concentrations, and then real-time monitoring instruments were used to measure the effect of using a diffusion dryer and thermodenuder for controlling moisture in a cleanroom. A polycarbonate filter sample was analyzed by field emission-scanning electron microscope (FE-SEM)-energy dispersive spectrometry to determine the particle morphology. The DLS intensity results for the three products showed a slightly right-shifted (~100 nm) bimodal distribution relative to the airborne particle size distribution. The size of the airborne PHMG particles increased during the spraying due to aggregation, with the particle size of aggregated particles confirmed by FE-SEM to be approximately ≥20 nm. As the PHMG concentration increased by 10 times, the airborne concentrations measured using a real-time monitoring instrument increased by 2–3 times for nanoparticles and 45–85 times for 1–10-μm particles during humidifier operation; however, 99% of the particles generated could be classified as PM1. Without ventilation, even after operating the humidifier, the PHMG particles could be airborne for approximately 2 h until the background concentration was reached. Therefore, we found that airborne behavior was affected by the PHMG concentration, but this did not vary according to product manufacturer. Second, LC-qToF was used to identify PHMG components in raw materials and airborne, and post-acquisition data processing was analyzed using UNIFI software. Samples in the air were diluted with the same conditions using three types of PHMGs to evaluate the behavioral characteristics (Chapter 2) at 8 h and had an impinger at 0.5 m and 1 m when the humidifier was sprayed. PHMG has been known to exist in the linear type (type A–C) and branched or cyclic type (type D–G). As a result of PHMG raw material analysis, various types existed, as shown in previous studies, among which the Oxy product was classified as type A–E, and BOC and Scunder products were classified as type A–E, except for type D. Additionally, the three products were composed of oligomers with 1–3 monomers, and compared to the linear type, dimer had the highest quantity in all products in type A and C. The linear structure in the Oxy product accounted for 90.6%, and Scunder and BOC products had linear structures of 78.6% and 75.8%, respectively. As the number of monomers increased (as the molecular weight increased), they were not detected at low concentrations. In a branched or cyclic structure, dimer of type E has the highest quantity in all products. In PHMG components of samples in the air, samples at 0.5 m showed a similar pattern with the component of raw materials, and dimers had the highest quantity in types A and C, and monomers in type B. However, high concentration samples collected at 1 m (65 ppm for Oxy product and 62.5 ppm and 125 ppm for Scunder and BOC products, respectively) were mainly detected for the low-molecular-weight compounds, such as monomer or dimer. Additionally, the concentration of the oligomer in air was estimated to be 35.89 µg/m3 at 6.5 ppm and 390.96 µg/m3 at 65 ppm for the Oxy product. Finally, based on data obtained in Chapter 2, inhaled and deposited doses were estimated using the ICRP and MPPD models. The ICRP model is widely used to evaluate the particle deposition in the respiratory tract for the general population and uses empirical equations based on experimental data, whereas the MPPD model is based on the ICRP model. Four types of scenarios were used in this study: adults and children and then daily and during sleep. Although the results of the two models varied due to differences in input parameters, the trend was similar. Infants and children tended to have similar or higher deposition doses and fractions than adults. Moreover, the areas of deposition were divided into the head airway, tracheobronchial, and alveolar regions. When the humidifier was sprayed, the highest number concentration was found at 15.4 nm, and the highest deposition fraction or dose by PM1 was noted in the pulmonary and head airways. Therefore, this study investigated the characteristics of raw materials of humidifier disinfectant containing PHMG sprayed in the air, and then estimated the inhaled and deposited dose in humans using the ICRP and MPPD models. Particles in raw materials of PHMG had a bimodal distribution in the region near 100 nm, and raw materials of PHMG consisted of oligomers in the linear type (type A–C). Characteristics of PHMG in the air were identified — most particles were PM1 and existed as aggregated single particles of approximately 20 nm in size. Aerosol had a high proportion of monomers, and the proportions of type C monomers were high at 1 m. Infants and young children showed high deposition doses or fractions in the ICRP and MPPD models. ; 겨울과 봄이 춥고 건조한 한국은 주로 초음파식 가습기를 많이 사용한다. 그러나 가습기 저장탱크 내 미생물 번식으로 인한 가습기 폐질환은 과거에 문제가 되어 왔기때문에 국내에서는 1994년부터 2011년까지 초음파 가습기의 미생물 오염을 막기 위하여 가습기 살균제를 사용해왔다. 하지만 2011년 가습기 살균제 사용자들에서 심각한 폐질환이 발생하여 현재는 정부에 의해 판매가 금지되었다. 가습기 살균제에 사용되는 주요 원료로는 polyhexamethyleneguanidine (PHMG), oligo(2-(2-ethoxy)ethoxyethyl guanidine chloride (PGH), methylchloroisothiazolinone /methylisothiazolinone (CMIT/MIT)가 있었고, 그 중 PHMG가 함유된 제품이 가장 많은 피해자가 발생하였다. 따라서 본 연구의 목적은 첫번째로 수용액에서의 PHMG 입자특성을 확인하고, 가습기 살균제로 사용된 PHMG의 공기 중 거동을 조사하는 것, 두번째로 고분자인 PHMG 제품과 공기 중 에어로졸에서 PHMG 단량체(oligomer) 유형과 함유량을 파악하고, 공기 중 노출 농도를 추정하는 것, 세번째로 공기 중 가습기 살균제 입자를 ICRP 모델을 이용하여 인체에 흡입노출 되었을 때 흡입량과 침착량을 추정하는 것이다. 먼저, 다양한 PHMG를 이용하여 실험하기 위해 제조사가 다른 PHMG (한국, 미국 및 중국에서 제조) 제품을 선택했다. 수용액에서의 거동 특성을 확인하기 위해 동적 광산란 장치(DLS)를 이용하였으며, 공기 중 특성은 PHMG를 희석하여 높은 농도 (62.5–65ppm)와 낮은 농도 (6.25–6.5ppm)로 희석한 후, 실시간 모니터링 장비(SMPS, OPS, PAS)로 측정하였다. 이때 클린룸 내 수분을 제어하기 위해 수분제어장치를(diffusion dryer, thermodenuder) 실시간 모니터링 장비에 장착하였다. 또한 공기 중 형태학적 입자특성을 확인하기 위하여 전자 현미경(FE-SEM-EDS)으로 분석하였다. DLS 결과는 공기 중 입자 분포에 비해 약간 오른쪽으로 치우친 (~ 100 nm) 이봉 분포(bimodal distribution)의 형태를 나타냈다. 전자현미경에 의해 확인 된 입자는 대략 20 nm 이상의 단일입자가 응집된 형태로 존재하였고, 공기 중에 분무되면서 PHMG 입자의 응집으로 크기가 증가된 것으로 추정된다. PHMG 원액 농도가 10 배 증가함에 따라, 실시간 모니터링 장비로 측정 한 공기 중 농도는 나노 입자의 경우 2–3 배, 1-10μm 입자의 경우 45–85 배 증가했다. 그러나 생성 된 입자의 99 %는 PM1이었다. 제조사에서 권장희석농도로(6.5 ppm) 가습기를 작동하고, 중단 한 이후에 환기를 하지 않는다면 배경 농도에 도달 할 때까지 PHMG 입자가 공기 중에 약 2 시간 존재할 수 있다. 따라서 PHMG 공기 중 거동특성은 제조업체가 다른 제품이라고 해서 크게 영향을 받지 않는 것으로 보인다. 두번째로, PHMG 구성 성분을 확인하기 위하여 LC-qToF를 이용하여 분석하였고, Unifi 프로그램을 이용하여 물질의 분자량과 구조를 고려하여 데이터 처리를 하였다. 가습기 분무 시 공기 중 샘플은 앞의 연구와 같은 조건으로 실험하였고, 샘플링은 임핀저를 이용하여 0.5 m와 1 m에서 8시간동안 채취하였다. PHMG 는 선형 타입(타입 A-C)과 가지 및 원형 타입 (타입 D-G)이 존재한다고 알려져 오고 있다. 원액분석결과 선행연구에서 알려진 것과 같이 다양한 타입이 존재하였고, 그 중 옥시 제품은 타입 A-E가 존재하였고, BOC와 Scunder 제품은 타입 A-E 중 타입 D를 제외하고 존재하였다. 또한 세 제품 구성성분 모두 단량체가 1-3개인 올리고머 수준으로 존재하였다. 공기 중에 분사된 PHMG 구성성분은 0.5 m 에서 채취된 샘플의 경우 원액구성성분과 유사한 패턴을 보였으나 농도가 낮거나 거리가 멀어지면(1 m) 주로 저분자인 단량체 (monomer, dimer)위주로 검출되었고, 주로 C 타입의 단량체인 monomer의 검출 비율이 높았다. 또한 공기 중 올리고머는 추정식을 이용하여 농도를 추정하였으며, 옥시제품의 권장희석배수인 200:1로 희석한 6.5 ppm에서 농도는 35.89 µg/m3 이었고, 65 ppm에서는 390.96 µg/m3 이었다. 마지막으로, 첫번째 연구인 실시간 기기로 측정한 공기 중 입자 농도 자료에 근거하여 인체 내 흡입 및 침착량을 ICRP 및 MPPD 흡입노출 모델을 사용하여 추정하였다. ICRP 모델은 일반 모집단의 폐에 침착되는 입자를 평가하는 데 널리 사용되며 실험 데이터를 기반한 실험식을 사용하며, 이것을 발전시켜 개발한 것인 MPPD 모델이다. 이 연구에서 4 가지 유형의 시나리오는 노출 집단은 성인과 어린이, 그리고 환경은 일상생활과 수면시의 조합으로 사용되었다. 입력변수의 차이로 인해 두 모델이 차이는 있으나, 성인이 어린이에 비해 침착량 및 및착분률이 유사하거나 높은 경향을 보인다. 침착량 산정시 기관지 내 침착부위는 3군데로 나뉘어 지는데, 머리기도, 기관지, 폐포 영역 각각의 노출량을 추정할 수 있다. 가습기가 분무 될 때, 15.4 nm에서 가장 높은 수농도의 침착량을 보였고, 질량농도에 의한 침착량은 두 모델 모두 폐포, 기관지, 머리기도 영역 순으로 높았다. 결론적으로, 본 연구는 가습기 살균제인 PHMG의 원액과 공기 중으로 분무 시 입자 특성을 확인 한 후 ICRP 모델을 이용하여 인체 호흡기 내 흡입 및 침착량을 추정하였다. PHMG 원액 입자는 100 nm 근처의 영역에서 이봉 분포를 보였고, 주 성분은 주로 선형 유형의 올리고머로 구성되었다(타입 A-C). 공기 중 PHMG의 특성은 대부분의 입자가 PM1이고 약 20-100 nm의 단일 입자가 응집 되어 존재하는 것으로 확인되었다. 공기 중 PHMG 에어로졸의 성분은 주로 올리고머 비율이 높았고, 0.5 m에서 측정된 샘플은 원액의 구성성분과 유사했으나 1 m에서 측정된 샘플은 단량체 중 타입 C가 높은 비율을 차지하였다. 따라서 공기 중 입자의 대부분은 저분자인 단량체(주로 monomer, dimer 등)가 나노입자로 응집되어 있는 형태로 존재한다. ICRP 및 MPPD 모델을 사용하여 추정 된 흡입 및 침착량은 영아 및 어린이의 개월 수가 낮을수록 높은 수치를 보였다. 본 연구에서 제조사가 다양한 PHMG 제품을 이용하여 실험한 결과 전체적으로 세 제품이 유사하였기 때문에, 옥시 제품 외 PHMG를 함유한 다른 가습기 살균제 제품도 본 연구와 유사한 결과를 보일 것으로 생각된다. ; CHAPTER I. 1 I-1. Hum Id If Ier d Is Infectant Inc Ident and the prev Ious stud Ies 2 I-2. Object Ives and study des Ign 7 CHAPTER II. 11 II-1. Introduct Ion 12 II-2. Methods 15 II-2-1. Preparat Ion of PHMG 15 II-2-2. Character Izat Ion of PHMG In aqueous solut Ion 17 II-2-3. Measurement and analys Is of a Irborne PHMG part Icles 18 II-3. Results 24 II-3-1. Character Ist Ics of PHMG In aqueous solut Ion 24 II-3-2. Behav Ioral character Ist Ics of a Irborne part Icles dur Ing and after hum Id If Ier operat Ion 26 II-3-3. F Ield em Iss Ion-scann Ing electron m Icroscope-energy d Ispers Ive spectrometry analys Is 40 II-4. D Iscuss Ion 42 II-5. Conclus Ions 50 CHAPTER III. 53 III-1. Introduct Ion 54 III-2. Mater Ials and Methods 56 III-2-1. Mater Ials 56 III-2-2. Sampl Ing of a Irborne PHMG 60 III-2-3. Analys Is of PHMG 63 III-3. Results 70 III-3-1. Character Ist Ics of raw mater Ials In PHMG products 70 III-3-2. Intens Ity and est Imated concentrat Ion of sample collected In the a Irborne 77 III-4. D Iscuss Ion 89 III-5. Conclus Ions 94 CHAPTER IV. 97 IV-1. Introduct Ion 98 IV-2. Methods 100 IV-2-1. Preparat Ion of PHMG 100 IV-2-2. Measurement of a Irborne PHMG part Icles 101 IV-2-3. Resp Iratory depos It Ion models 105 IV-3. Results 114 IV-3-1. ICRP model 114 IV-3-2. MPPD model 124 IV-4. D Iscuss Ion 131 IV-5. Conclus Ions 134 CHAPTER V. 137 REFERENCES 141 APPEND ICES 150 국문 초록 166 ; Doctor