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Journal articles on the topic 'Apportionments'

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Author: Grafiati

Published: 4 May 2024

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1

Chatani, Satoru, Hikari Shimadera, Syuichi Itahashi, and Kazuyo Yamaji. "Comprehensive analyses of source sensitivities and apportionments of PM<sub>2.5</sub> and ozone over Japan via multiple numerical techniques." Atmospheric Chemistry and Physics 20, no. 17 (September 4, 2020): 10311–29. http://dx.doi.org/10.5194/acp-20-10311-2020.

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Abstract. Source sensitivity and source apportionment are two major indicators representing source–receptor relationships, which serve as essential information when considering effective strategies to accomplish improved air quality. This study evaluated source sensitivities and apportionments of ambient ozone and PM2.5 concentrations over Japan with multiple numerical techniques embedded in regional chemical transport models, including a brute-force method (BFM), a high-order decoupled direct method (HDDM), and an integrated source apportionment method (ISAM), to update the source–receptor relationships considering stringent emission controls recently implemented in Japan and surrounding countries. We also attempted to understand the differences among source sensitivities and source apportionments calculated by multiple techniques. While a part of ozone concentrations was apportioned to domestic sources, their sensitivities were small or even negative; ozone concentrations were exclusively sensitive to transport from outside Japan. Although the simulated PM2.5 concentrations were significantly lower than those reported by previous studies, their sensitivity to transport from outside Japan was still relatively large, implying that there has been a reduction in Japanese emissions, similar to surrounding countries including China, due to implementation of stringent emission controls. HDDM allowed us to understand the importance of the non-linear responses of PM2.5 concentrations to precursor emissions. Apportionments derived by ISAM were useful in distinguishing various direct and indirect influences on ozone and PM2.5 concentrations by combining with sensitivities. The results indicate that ozone transported from outside Japan plays a key role in exerting various indirect influences on the formation of ozone and secondary PM2.5 components. While the sensitivities come closer to the apportionments when perturbations in emissions are larger in highly non-linear relationships – including those between NH3 emissions and NH4+ concentrations, NOx emissions and NO3- concentrations, and NOx emissions and ozone concentrations – the sensitivities did not reach the apportionments because there were various indirect influences including other sectors, complex photochemical reactions, and gas–aerosol partitioning. It is essential to consider non-linear influences to derive strategies for effectively suppressing concentrations of secondary pollutants.

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2

Gari, Yared, Paul Block, Tammo S. Steenhuis, Muluneh Mekonnen, Getachew Assefa, Abebe Kidus Ephrem, Yared Bayissa, and Seifu A. Tilahun. "Developing an Approach for Equitable and Reasonable Utilization of International Rivers: The Nile River." Water 15, no. 24 (December 18, 2023): 4312. http://dx.doi.org/10.3390/w15244312.

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The absence of a basin-wide apportionment agreement on using the Nile River equitably has been a long-standing source of disagreement among Nile riparian states. This study introduces a new approach that the riparian states can consider that quantifies the Nile River’s apportionment. The approach includes (1) developing a basin-wide database of indicators representative of the United Nations Watercourse Convention (UNWC) relevant factors and circumstances, (2) developing an ensemble of indicator weighting scenarios using various weighting methods, and (3) developing six water-sharing methods to obtain a range of apportionments for Egypt, Sudan, Ethiopia and the group of the White Nile Equatorial States for each weighting scenarios. The results illustrate a relatively narrow range of country-level water apportionments, even though some individual factor weights vary from 3% to 26%. Considering the entire Nile River, the water apportionment for Ethiopia ranges from 32% to 38%, Sudan and South Sudan from 25% to 33%, Egypt from 26% to 35%, and the Equatorial States from 5% to 7%. We trust that the six proposed equitable water-sharing methods may aid in fostering basin-wide negotiations toward a mutual agreement and address the dispute over water sharing.

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3

Haman, Jacek. "THE CONCEPT OF DEGRESSIVE AND PROGRESSIVE PROPORTIONALITY AND ITS NORMATIVE AND DESCRIPTIVE APPLICATIONS." Studies in Logic, Grammar and Rhetoric 50, no. 1 (June 27, 2017): 67–91. http://dx.doi.org/10.1515/slgr-2017-0019.

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Abstract The article discusses the concept of progressive and degressive proportionality of the distribution of parliamentary seats. In the first part are presented axiological sources of the principles of proportionality and progressive and degressive proportionality and the history of degressively proportional apportionments of seats in the European Parliament. The main part of the article is devoted to the formulation of proposals for strict formal definition of degressive and progressive proportionality, and a description of the method of apportionment of seats in the European Parliament based on the strict definition of degressive proportionality and maintaining maximum compatibility with former apportionments adopted in multilateral negotiations. The last part of the article consists of a discussion of the possibilities of adopting the concept of progressive proportionality in the analysis of the functioning of parliamentary electoral systems.

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4

Bolun, Ion. "Degree of favoring in apportionments." Computer Science Journal of Moldova 30, no. 2 (89) (July 2022): 187–213. http://dx.doi.org/10.56415/csjm.v30.11.

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To quantitatively estimate the degree of favoring the beneficiaries in proportional apportionments of entities of the same kind (seats, PCs, etc.), five quantitative criteria were defined. By computer simulation, the degree of favoring the large or small beneficiaries by 6 apportionment methods is identified. Thus, favoring large beneficiaries by the d’Hondt method can overpass 10.7-12.1 entities (entities in excess) and that of small beneficiaries by the Huntington-Hill method -- 2.7-11.0 entities, and by the Adapted Sainte-Lagu\"{e} method -- 1.7-9.7 entities. The Huntington-Hill method favors small beneficiaries up to 5.70 times stronger than the Adapted Sainte-Laguë one does. Also, the d’Hondt method favors beneficiaries (the large ones) much stronger than the Adapted Sainte-Laguë one does (the small ones) -- for very many cases the respective ratio exceeds 10 times.

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5

Edelman, Paul H. "Voting power apportionments." Social Choice and Welfare 44, no. 4 (February 1, 2015): 911–25. http://dx.doi.org/10.1007/s00355-015-0869-4.

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6

Chatani, Satoru, Kazuyo Yamaji, Tatsuya Sakurai, Syuichi Itahashi, Hikari Shimadera, Kyo Kitayama, and Hiroshi Hayami. "Overview of Model Inter-Comparison in Japan’s Study for Reference Air Quality Modeling (J-STREAM)." Atmosphere 9, no. 1 (January 11, 2018): 19. http://dx.doi.org/10.3390/atmos9010019.

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The inter-comparison of regional air quality models is an effective way to understand uncertainty in ambient pollutant concentrations simulated using various model configurations, as well as to find ways to improve model performance. Based on the outcomes and experiences of Japanese projects thus far, a new model inter-comparison project called Japan’s study for reference air quality modeling (J-STREAM) has begun. The objective of J-STREAM is to establish reference air quality modeling for source apportionment and effective strategy making to suppress secondary air pollutants including PM2.5 and photochemical ozone in Japan through model inter-comparison. The first phase focuses on understanding the ranges and limitations in ambient PM2.5 and ozone concentrations simulated by participants using common input datasets. The second phase focuses on issues revealed in previous studies in simulating secondary inorganic aerosols, as well as on the three-dimensional characteristics of photochemical ozone as a new target. The third phase focuses on comparing source apportionments and sensitivities under heavy air pollution episodes simulated by participating models. Detailed understanding of model performance, uncertainty, and possible improvements to urban-scale air pollution involving secondary pollutants, as well as detailed sector-wise source apportionments over megacities in Japan are expected.

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7

Yang, Zhiyi, Md Kamrul Islam, Tian Xia, and Stuart Batterman. "Apportionment of PM2.5 Sources across Sites and Time Periods: An Application and Update for Detroit, Michigan." Atmosphere 14, no. 3 (March 20, 2023): 592. http://dx.doi.org/10.3390/atmos14030592.

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Identifying sources of air pollutants is essential for informing actions to reduce emissions, exposures, and adverse health impacts. This study updates and extends apportionments of particulate matter (PM2.5) in Detroit, MI, USA, an area with extensive industrial, vehicular, and construction activity interspersed among vulnerable communities. We demonstrate an approach that uses positive matrix factorization models with combined spatially and temporally diverse datasets to assess source contributions, trend seasonal levels, and examine pandemic-related effects. The approach consolidates measurements from 2016 to 2021 collected at three sites. Most PM2.5 was due to mobile sources, secondary sulfate, and secondary nitrate; smaller contributions arose from soil/dust, ferrous and non-ferrous metals, and road salt sources. Several sources varied significantly by season and site. Pandemic-related changes were generally modest. Results of the consolidated models were more consistent with respect to trends and known sources, and the larger sample size should improve representativeness and stability. Compared to earlier apportionments, contributions of secondary sulfate and nitrate were lower, and mobile sources now represent the dominant PM2.5 contributor. We show the growing contribution of mobile sources, the need to update apportionments performed just 5–10 years ago, and that apportionments at a single site may not apply elsewhere in the same urban area, especially for local sources.

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8

Batista, P. V. G., J. P. Laceby, and O. Evrard. "How to evaluate sediment fingerprinting source apportionments." Journal of Soils and Sediments 22, no. 4 (February 9, 2022): 1315–28. http://dx.doi.org/10.1007/s11368-022-03157-4.

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Abstract Purpose Evaluating sediment fingerprinting source apportionments with artificial mixtures is crucial for supporting decision-making and advancing modeling approaches. However, artificial mixtures are rarely incorporated into fingerprinting research and guidelines for model testing are currently lacking. Here, we demonstrate how to test source apportionments using laboratory and virtual mixtures by comparing the results from Bayesian and bootstrapped modeling approaches. Materials and methods Laboratory and virtual mixtures (n = 79) with known source proportions were created with soil samples from two catchments in Fukushima Prefecture, Japan. Soil samples were sieved at 63 µm and analyzed for colorimetric and geochemical parameters. The MixSIAR Bayesian framework and a bootstrapped mixing model (BMM) were used to estimate source contributions to the artificial mixtures. In addition, we proposed and demonstrated the use of multiple evaluation metrics to report on model uncertainty, residual errors, performance, and contingency criteria. Results and discussion Overall, there were negligible differences between source apportionments for the laboratory and virtual mixtures, for both models. The comparison between MixSIAR and BMM illustrated a trade-off between accuracy and precision in the model results. The more certain MixSIAR solutions encompassed a lesser proportion of known source values, whereas the BMM apportionments were markedly less precise. Although model performance declined for mixtures with a single source contributing greater than 0.75 of the material, both models represented the general trends in the mixtures and identified their major sources. Conclusions Virtual mixtures are as robust as laboratory mixtures for assessing fingerprinting mixing models if analytical errors are negligible. We therefore recommend to always include virtual mixtures as part of the model testing process. Additionally, we highlight the value of using evaluation metrics that consider the accuracy and precision of model results, and the importance of reporting uncertainty when modeling source apportionments.

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9

Argersinger, Peter H. "All Politics Are Local: Another Look at the 1890s." Journal of the Gilded Age and Progressive Era 8, no. 1 (January 2009): 7–24. http://dx.doi.org/10.1017/s1537781400000979.

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Although rarely considered by historians, legislative and congressional apportionments were among the most important, absorbing, and contentious political issues of the late nineteenth century. Local, state, and national party leaders struggled to shape apportionments and thereby secure disproportionate influence for the counties, districts, and states their followers controlled. Gerrymanders, in turn, not only distorted representation but often incited a furious opposition, which disrupted legislative bodies, transformed political campaigns, and ultimately produced unprecedented judicial intervention. In surveying these overlooked developments, this essay points to important questions that historians must hereafter address.

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10

Zhou, Chuanlong, Hao Zhou, Philip K. Hopke, and Thomas M. Holsen. "Overview of the Trajectory-Ensemble Potential Source Apportionment Web (TraPSA-Web) Toolkit for Atmospheric Pollutant Source Identification." Atmosphere 15, no. 2 (January 30, 2024): 176. http://dx.doi.org/10.3390/atmos15020176.

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Trajectory ensemble receptor models (TERMs) were widely used to determine the likely source locations and apportionment of air pollutants. This paper describes the development and applications of the Trajectory-ensemble Potential Source Apportionment Web application (TraPSA-Web), a comprehensive toolkit for likely atmospheric pollutant source location apportionments using TERMs and back trajectories generated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The TERMs integrated within the TraPSA-web include Concentration Field Analysis (CFA), Concentration Weighted Trajectory (CWT), single-site and multiple-site Potential Source Contribution Function (PSCF), and Simplified Quantitative Transport Bias Analysis (SQBA). TraPSA-Web is designed as a web application with a user-friendly modern graphical user interface (GUI), which largely enhances the accessibility to the users. TraPSA-Web will provide the air quality research community with a sophisticated toolkit for (1) easy management of the research project and datasets, (2) efficient automatization for HYSPLIT configurations, calculations, and result aggregations, (3) flexible configurations for the research scenarios and TERM parameters, and (4) interactive visualizations for the pollutant pattern analysis and TERM result mapping.

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11

Kong, Xueqian, Hexiang Deng, Fangyong Yan, Jihan Kim, Joseph A. Swisher, Berend Smit, Omar M. Yaghi, and Jeffrey A. Reimer. "Mapping of Functional Groups in Metal-Organic Frameworks." Science 341, no. 6148 (July 25, 2013): 882–85. http://dx.doi.org/10.1126/science.1238339.

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We determined the heterogeneous mesoscale spatial apportionment of functional groups in a series of multivariate metal-organic frameworks (MTV-MOF-5) containing BDC (1,4-benzenedicarboxylate) linkers with different functional groups—B (BDC-NH2), E (BDC-NO2), F [(BDC-(CH3)2], H [BDC-(OC3H5)2], and I [BDC-(OC7H7)2]—using solid-state nuclear magnetic resonance measurements combined with molecular simulations. Our analysis reveals that these methods discern between random (EF), alternating (EI and EHI), and various cluster (BF) forms of functional group apportionments. This combined synthetic, characterization, and computational approach predicts the adsorptive properties of crystalline MTV-MOF systems. This methodology, developed in the context of ordered frameworks, is a first step in resolving the more general problem of spatial disorder in other ordered materials, including mesoporous materials, functionalized polymers, and defect distributions within crystalline solids.

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12

Saari, D. G. "Chaos, but in voting and apportionments?" Proceedings of the National Academy of Sciences 96, no. 19 (September 14, 1999): 10568–71. http://dx.doi.org/10.1073/pnas.96.19.10568.

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13

Serafini, Paolo. "Certificates of optimality for minimum norm biproportional apportionments." Social Choice and Welfare 44, no. 1 (May 22, 2014): 1–12. http://dx.doi.org/10.1007/s00355-014-0821-z.

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14

DEMANGE, GABRIELLE. "ON ALLOCATING SEATS TO PARTIES AND DISTRICTS: APPORTIONMENTS." International Game Theory Review 15, no. 03 (July 29, 2013): 1340014. http://dx.doi.org/10.1142/s0219198913400148.

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The paper presents the problem of choosing the representatives in an assembly when the whole electoral region is subdivided into several electoral districts. Because of the two dimensions, geographical (districts) and political (parties), the problem is called bi-apportionment. The main purpose of the paper is to discuss fairness and proportionality axioms and to describe their implementation.

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15

Thunis, Philippe, Alain Clappier, Alexander de Meij, Enrico Pisoni, Bertrand Bessagnet, and Leonor Tarrason. "Why is the city's responsibility for its air pollution often underestimated? A focus on PM<sub>2.5</sub>." Atmospheric Chemistry and Physics 21, no. 24 (December 15, 2021): 18195–212. http://dx.doi.org/10.5194/acp-21-18195-2021.

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Abstract. While the burden caused by air pollution in urban areas is well documented, the origin of this pollution and therefore the responsibility of the urban areas in generating this pollution are still a subject of scientific discussion. Source apportionment represents a useful technique to quantify the city's responsibility, but the approaches and applications are not harmonized and therefore not comparable, resulting in confusing and sometimes contradicting interpretations. In this work, we analyse how different source apportionment approaches apply to the urban scale and how their building elements and parameters are defined and set. We discuss in particular the options available in terms of indicator, receptor, source, and methodology. We show that different choices for these options lead to very large differences in terms of outcome. For the 150 large EU cities selected in our study, different choices made for the indicator, the receptor, and the source each lead to an average difference of a factor of 2 in terms of city contribution. We also show that temporal- and spatial-averaging processes applied to the air quality indicator, especially when diverging source apportionments are aggregated into a single number, lead to the favouring of strategies that target background sources while occulting actions that would be efficient in the city centre. We stress that methodological choices and assumptions most often lead to a systematic and important underestimation of the city's responsibility, with important implications. Indeed, if cities are seen as a minor actor, plans will target the background as a priority at the expense of potentially effective local actions.

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16

Gonzalez, J., and N. Lacourly. "A family of Hamilton type methods for congressional apportionments." RAIRO - Operations Research 26, no. 1 (1992): 31–40. http://dx.doi.org/10.1051/ro/1992260100311.

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17

Liu, Shijing, Hongyu Jin, Chunlu Liu, Benzheng Xie, and Anthony Mills. "Investment apportionments among participants of PPP rental retirement villages." Built Environment Project and Asset Management 10, no. 1 (November 28, 2019): 64–77. http://dx.doi.org/10.1108/bepam-02-2019-0018.

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Purpose The purpose of this paper is to examine public–private partnership (PPP) approaches for the construction of rental retirement villages in Australia and to allocate the investment proportions under a certain project return rate among three investors which are the government, private sectors and pension funds. The apportionment will achieve a minimum overall investment risk for the project. Design/methodology/approach Capital structure, particularly determination of investment apportionment proportions, is one of the key factors affecting the success of PPP rental retirement villages. Markowitz mean-variance model was applied to examine the investment allocations with minimum project investment risks under a certain projected return rate among the PPP partners for the construction of rental retirement villages. Findings The research findings validate the feasibility of the inclusion of pension funds in the construction of PPP rental retirement villages and demonstrate the existence of relationships between the project return rate and the investment allocation proportions. Originality/value This paper provides a quantitative approach for determination of the investment proportions among PPP partners to enrich the theory of PPP in relation to the construction of rental retirement villages. This has implications for PPP partners and can help these stakeholders make vital contributions in developing intellectual wealth in the PPP investment area while providing them with a detailed guide to decision making and negotiation in relation to investment in PPP rental retirement villages.

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18

ALDAPE, F., and J. FLORES M. "SOURCE APPORTIONMENT OF FINE AIRBORNE PARTICULATE MATTER COLLECTED IN THE MEXICO CITY METROPOLITAN AREA." International Journal of PIXE 14, no. 03n04 (January 2004): 147–60. http://dx.doi.org/10.1142/s0129083504000215.

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Samples of fine airborne particulate matter ( PM 2.0) have been collected at three sites located in the Mexico City Metropolitan Area (MCMA) during July, August, and September 2000. The elemental concentrations of these samples were determined by PIXE so that twelve elements ( S , Cl , K , Ca , Ti , Mn , Fe , Ni , Cu , Zn , Br and Pb ) were consistently detected. These results produced a database, which was statistically analysed; first by Principal Components so to identify the pollution sources, and, subsequently, by Absolute Principal Component Scores analysis in order to estimate the corresponding source apportionment contributions. Other elements such as V and Cr were also detected in around 20% of the samples and, therefore, they were not considered statistically significant. Thus, these elements, as well as some others found only occasionally and in the trace range, were left out of the discussion. All calculations were performed using a standard statistical package following the method developed by Thurston and Spengler. Four main pollution sources were identified and the source apportionments were found in good agreement with other estimations found in the literature. The results were obtained individually for the three sampling sites, but the complete results are presented for just one of the sites in order to simplify this presentation.

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19

Malhotra, Kritika, Jingyi Zheng, Ash Abebe, and Jasmeet Lamba. "Application of Sediment Fingerprinting to Apportion Sediment Sources: Using Machine Learning Models." Journal of the ASABE 66, no. 5 (2023): 1205–21. http://dx.doi.org/10.13031/ja.14906.

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Highlights Relative source contributions to stream bed sediment from construction sites and stream banks were quantified. Two machine-learning techniques were used to select composite fingerprinting properties. The MixSIR Bayesian model was employed for source apportionment. Statistical methods employed for fingerprinting properties selection have the potential to impact source apportionments. Management strategies to reduce sediment mobilization should be targeted depending on the dominant source of sediment in each sub-watershed. Abstract. Sediment fingerprinting is an extensively used approach for investigating sediment sources by linking in-stream sediment mixtures with watershed source materials. The overall goal of this research was to estimate the relative source contributions of stream banks and construction sites to the stream bed sediment in an urbanized watershed (Alabama, USA) using a fingerprinting technique established on composite fingerprints selected by two different machine learning techniques at a sub-watershed scale. The two statistical approaches employed to select the subset of fingerprinting properties were: (1) the Random Forest algorithm (RF) with Gini importance ranking of variables; and (2) logistic regression with the least absolute shrinkage and selection operator (LASSO). A Bayesian mixing model was then used to estimate the distribution of mixing proportions along with the associated uncertainty. The models were built based on the composite fingerprints selected using the two machine learning methods. Overall, using the subset of fingerprints selected by RF and LASSO, the relative contribution of stream banks ranged from 14±9% to 97±2% and from 24±18% to 94±5%, respectively, throughout the watershed. The stream bank contributions were compared with a previous study conducted in the watershed that utilized a two-step statistical procedure (which involved a Mann-Whitney U-test as the first step and discriminant function analysis (DFA) as the second step) to select the composite of fingerprinting properties and a frequentist mixing model to calculate the source apportionments. The relative contributions of stream banks to stream bed sediment in the previous study reported ranged from 9±8% to 100±1%. Therefore, the study demonstrated the dependence of source attributions on the statistical procedures used to select the optimum composite fingerprints for sediment fingerprinting applications. Furthermore, the results underscored the importance of using different mixing model structures to obtain reliable estimates of source contributions. Keywords: Least absolute shrinkage and selection operator (LASSO), MixSIR Bayesian model, Random Forest (RF), Statistical techniques.

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20

Hopke, Philip K., Qili Dai, Linxuan Li, and Yinchang Feng. "Global review of recent source apportionments for airborne particulate matter." Science of The Total Environment 740 (October 2020): 140091. http://dx.doi.org/10.1016/j.scitotenv.2020.140091.

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21

Nepal, Sakar, T. Eric McConnell, Alan Barefield, and Robert Grala. "Mississippi USA'S timber severance tax apportionments and their economic contributions." Forest Policy and Economics 157 (December 2023): 103086. http://dx.doi.org/10.1016/j.forpol.2023.103086.

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22

Milando, Chad, Lei Huang, and Stuart Batterman. "Trends in PM2.5 emissions, concentrations and apportionments in Detroit and Chicago." Atmospheric Environment 129 (March 2016): 197–209. http://dx.doi.org/10.1016/j.atmosenv.2016.01.012.

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23

TSAI, Y., and C. CHEN. "Atmospheric aerosol composition and source apportionments to aerosol in southern Taiwan." Atmospheric Environment 40, no. 25 (August 2006): 4751–63. http://dx.doi.org/10.1016/j.atmosenv.2006.04.029.

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Pretolani, Daniele. "Apportionments with minimum Gini index of disproportionality: a Quadratic Knapsack approach." Annals of Operations Research 215, no. 1 (April 24, 2013): 257–67. http://dx.doi.org/10.1007/s10479-013-1383-7.

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25

Han, Tingting, Xingang Liu, Yuanhang Zhang, Yu Qu, Jianwei Gu, Qiang Ma, Keding Lu, et al. "Characteristics of Aerosol Optical Properties and Their Chemical Apportionments during CAREBeijing 2006." Aerosol and Air Quality Research 14, no. 5 (2014): 1431–42. http://dx.doi.org/10.4209/aaqr.2013.06.0203.

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26

Lowenthal, Douglas H., and Kenneth A. Rahn. "Reproducibility of regional apportionments of pollution aerosol in the Northeastern United States." Atmospheric Environment (1967) 22, no. 9 (January 1988): 1829–33. http://dx.doi.org/10.1016/0004-6981(88)90070-4.

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27

Bozzetti, Carlo, Imad El Haddad, Dalia Salameh, Kaspar Rudolf Daellenbach, Paola Fermo, Raquel Gonzalez, María Cruz Minguillón, et al. "Organic aerosol source apportionment by offline-AMS over a full year in Marseille." Atmospheric Chemistry and Physics 17, no. 13 (July 7, 2017): 8247–68. http://dx.doi.org/10.5194/acp-17-8247-2017.

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Abstract. We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France), which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). In total 216 PM2. 5 (particulate matter with an aerodynamic diameter < 2.5 µm) filter samples were collected over 1 year from August 2011 to July 2012. These filters were used to create 54 composite samples which were analyzed by offline-AMS. The same samples were also analyzed for major water-soluble ions, metals, elemental and organic carbon (EC ∕ OC), and organic markers, including n-alkanes, hopanes, polycyclic aromatic hydrocarbons (PAHs), lignin and cellulose pyrolysis products, and nitrocatechols. The application of positive matrix factorization (PMF) to the water-soluble AMS spectra enabled the extraction of five factors, related to hydrocarbon-like OA (HOA), cooking OA (COA), biomass burning OA (BBOA), oxygenated OA (OOA), and an industry-related OA (INDOA). Seasonal trends and relative contributions of OA sources were compared with the source apportionment of OA spectra collected from the AMS field deployment at the same station but in different years and for shorter monitoring periods (February 2011 and July 2008). Online- and offline-AMS source apportionment revealed comparable seasonal contribution of the different OA sources. Results revealed that BBOA was the dominant source during winter, representing on average 48 % of the OA, while during summer the main OA component was OOA (63 % of OA mass on average). HOA related to traffic emissions contributed on a yearly average 17 % to the OA mass, while COA was a minor source contributing 4 %. The contribution of INDOA was enhanced during winter (17 % during winter and 11 % during summer), consistent with an increased contribution from light alkanes, light PAHs (fluoranthene, pyrene, phenanthrene), and selenium, which is commonly considered as a unique coal combustion and coke production marker. Online- and offline-AMS source apportionments revealed evolving levoglucosan : BBOA ratios, which were higher during late autumn and March. A similar seasonality was observed in the ratios of cellulose combustion markers to lignin combustion markers, highlighting the contribution from cellulose-rich biomass combustion, possibly related to agricultural activities.

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Franzé, Roberto. "Transfer Pricing and Distribution Arrangements: From Arm’s Length to Formulary Apportionments of Income." Intertax 33, Issue 6/7 (June 1, 2005): 260–65. http://dx.doi.org/10.54648/taxi2005047.

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29

Heo, Jongbae, Bo Wu, Ziad Abdeen, Radwan Qasrawi, Jeremy A. Sarnat, Geula Sharf, Kobby Shpund, and James J. Schauer. "Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities." Environmental Pollution 225 (June 2017): 1–11. http://dx.doi.org/10.1016/j.envpol.2017.01.081.

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Ling, Z. H., H. Guo, I. J. Simpson, S. M. Saunders, S. H. M. Lam, X. P. Lyu, and D. R. Blake. "New insight into the spatiotemporal variability and source apportionments of C<sub>1</sub>–C<sub>4</sub> alkyl nitrates in Hong Kong." Atmospheric Chemistry and Physics Discussions 15, no. 16 (August 24, 2015): 22597–636. http://dx.doi.org/10.5194/acpd-15-22597-2015.

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Abstract. Alkyl nitrates (RONO2) were measured concurrently at a mountain site (TMS) and an urban site (TW) at the foot of the same mountain in Hong Kong from September to November 2010, when high O3 mixing ratios were frequently observed. The abundance and temporal patterns of five C1–C4 RONO2 and their parent hydrocarbons (RH), the RONO2/RH ratios and photochemical age of air masses at TMS differed from those at TW, reflecting different contributions of direct emissions and secondary formation of RONO2 at the two sites. Relative to 2-BuONO2/n-butane, the measured ratios of C1–C2 RONO2/RH at the two sites exhibited significant positive deviations from pure photochemical (PP) curves and background initial ratio (BIR) curves obtained from laboratory kinetic data, suggesting that background mixing ratios had a significant influence on the RONO2 and RH distributions. In contrast to the C1–C2 RONO2/RH ratios, the evolution for the measured ratios of C3 RONO2/RH to 2-BuONO2/n-butane agreed well with the ratio distributions in the PP and BIR curves at the two sites. Furthermore, the ratios of 1-/2-PrONO2 and yields of 1- and 2-PrONO2 suggested that the C3 RONO2 were mainly from secondary formation at TMS, whereas secondary formation and other additional sources had a significant influence on C3 RONO2 mixing ratios at TW. The source apportionment results confirmed that secondary formation was the dominant contributor to all the RONO2 at TMS, while most of the RONO2 at TW were from secondary formation and biomass burning. The findings of the source apportionments and photochemical evolution of RONO2 are helpful to evaluate photochemical processing in Hong Kong using RONO2 as an indicator.

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El Haddad, I., B. D'Anna, B. Temime-Roussel, M. Nicolas, A. Boreave, O. Favez, D. Voisin, et al. "Towards a better understanding of the origins, chemical composition and aging of oxygenated organic aerosols: case study of a Mediterranean industrialized environment, Marseille." Atmospheric Chemistry and Physics 13, no. 15 (August 15, 2013): 7875–94. http://dx.doi.org/10.5194/acp-13-7875-2013.

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Abstract. As part of the FORMES summer 2008 experiment, an Aerodyne compact time-of-flight aerosol mass spectrometer (cToF-AMS) was deployed at an urban background site in Marseille to investigate the sources and aging of organic aerosols (OA). France's second largest city and the largest port in the Mediterranean, Marseille, provides a locale that is influenced by significant urban industrialized emissions and an active photochemistry with very high ozone concentrations. Particle mass spectra were analyzed by positive matrix factorization (PMF2) and the results were in very good agreement with previous apportionments obtained using a chemical mass balance (CMB) approach coupled to organic markers and metals (El Haddad et al., 2011a). AMS/PMF2 was able to identify for the first time, to the best of our knowledge, the organic aerosol emitted by industrial processes. Even with significant industries in the region, industrial OA was estimated to contribute only ~ 5% of the total OA mass. Both source apportionment techniques suggest that oxygenated OA (OOA) constitutes the major fraction, contributing ~ 80% of OA mass. A novel approach combining AMS/PMF2 data with 14C measurements was applied to identify and quantify the fossil and non-fossil precursors of this fraction and to explicitly assess the related uncertainties. Results show with high statistical confidence that, despite extensive urban and industrial emissions, OOA is overwhelmingly non-fossil, formed via the oxidation of biogenic precursors, including monoterpenes. AMS/PMF2 results strongly suggest that the variability observed in the OOA chemical composition is mainly driven in our case by the aerosol photochemical age. This paper presents the impact of photochemistry on the increase of OOA oxygenation levels, formation of humic-like substances (HULIS) and the evolution of α-pinene SOA (secondary OA) components.

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Pasha, Obed. "Social justice implications of municipal transportation apportionments in Massachusetts: A case of disparate impact." Transport Policy 72 (December 2018): 109–15. http://dx.doi.org/10.1016/j.tranpol.2018.10.001.

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El Haddad, I., N. Marchand, H. Wortham, C. Piot, J. L. Besombes, J. Cozic, C. Chauvel, A. Armengaud, D. Robin, and J. L. Jaffrezo. "Primary sources of PM<sub>2.5</sub> organic aerosol in an industrial Mediterranean city, Marseille." Atmospheric Chemistry and Physics 11, no. 5 (March 7, 2011): 2039–58. http://dx.doi.org/10.5194/acp-11-2039-2011.

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Abstract. Marseille, the most important port of the Mediterranean Sea, represents a challenging case study for source apportionment exercises, combining an active photochemistry and multiple emission sources, including fugitive emissions from industrial sources and shipping. This paper presents a Chemical Mass Balance (CMB) approach based on organic markers and metals to apportion the primary sources of organic aerosol in Marseille, with a special focus on industrial emissions. Overall, the CMB model accounts for the major primary anthropogenic sources including motor vehicles, biomass burning and the aggregate emissions from three industrial processes (heavy fuel oil combustion/shipping, coke production and steel manufacturing) as well as some primary biogenic emissions. This source apportionment exercise is well corroborated by 14C measurements. Primary OC estimated by the CMB accounts on average for 22% of total OC and is dominated by the vehicular emissions that contribute on average for 17% of OC mass concentration (vehicular PM contributes for 17% of PM2.5). Even though industrial emissions contribute only 2.3% of the total OC (7% of PM2.5), they are associated with ultrafine particles (Dp<80 nm) and high concentrations of Polycyclic Aromatic Hydrocarbons (PAH) and heavy metals such as Pb, Ni and V. On one hand, given that industrial emissions governed key primary markers, their omission would lead to substantial uncertainties in the CMB analysis performed in areas heavily impacted by such sources, hindering accurate estimation of non-industrial primary sources and secondary sources. On the other hand, being associated with bursts of submicron particles and carcinogenic and mutagenic components such as PAH, these emissions are most likely related with acute ill-health outcomes and should be regulated despite their small contributions to OC. Another important result is the fact that 78% of OC mass cannot be attributed to the major primary sources and, thus, remains un-apportioned. We have consequently critically investigated the uncertainties underlying our CMB apportionments. While we have provided some evidence for photochemical decay of hopanes, this decay does not appear to significantly alter the CMB estimates of the total primary OC. Sampling artifacts and unaccounted primary sources also appear to marginally influence the amount of un-apportioned OC. Therefore, this significant amount of un-apportioned OC is mostly attributed to secondary organic carbon that appears to be the major component of OC during the whole period of study.

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Bae, Minah, Eunhye Kim, Seunghee You, Kyuwon Son, Yoon-Hee Kang, and Soontae Kim. "Local Authority Level Source Apportionments of PM2.5 Concentrations based on the CAPSS 2016: (VII) Seoul." Journal of Korean Society for Atmospheric Environment 37, no. 3 (June 30, 2021): 466–86. http://dx.doi.org/10.5572/kosae.2021.37.3.466.

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35

Fan, Mei-Yi, Yan-Lin Zhang, Yu-Chi Lin, Lin Li, Feng Xie, Jianlin Hu, Ahsan Mozaffar, and Fang Cao. "Source apportionments of atmospheric volatile organic compounds in Nanjing, China during high ozone pollution season." Chemosphere 263 (January 2021): 128025. http://dx.doi.org/10.1016/j.chemosphere.2020.128025.

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36

El Haddad, I., N. Marchand, H. Wortham, C. Piot, J. L. Besombes, J. Cozic, C. Chauvel, A. Armengaud, D. Robin, and J. L. Jaffrezo. "Primary sources of PM<sub>2.5</sub> organic aerosol in an industrial Mediterranean city, Marseille." Atmospheric Chemistry and Physics Discussions 10, no. 11 (November 1, 2010): 25435–90. http://dx.doi.org/10.5194/acpd-10-25435-2010.

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Abstract. Marseille, the most important port of the Mediterranean Sea, represents a challenging case study for source apportionment exercises, combining an active photochemistry and multiple emission sources, including fugitive emissions from industrial sources and shipping. This paper presents a Chemical Mass Balance (CMB) approach based on organic markers and metals to apportion the primary sources of organic aerosol in Marseille, with a special focus on industrial emissions. Overall, the CMB model accounts for the major primary anthropogenic sources including motor vehicles, biomass burning, and the aggregate emissions from three industrial processes (HFO combustion/shipping, coke production and steel manufacturing) as well as some primary biogenic emissions. This source apportionment exercise is well corroborated by 14C measurements. Primary OC estimated by the CMB accounts on average for 22% and is dominated by the vehicular emissions that contribute on average for 17% of OC mass concentration (17% of PM2.5). Even though, industrial emissions contribute for only 2.3% of the total OC (7% of PM2.5), they are associated with ultrafine particles (Dp<80 nm) and high concentrations of Polycyclic Aromatic Hydrocarbons (PAH) and heavy metals such as Pb, Ni and V. On one hand, given that industrial emissions governed key primary markers, their omission would lead to substantial uncertainties in the CMB analysis performed in areas heavily impacted by such sources, hindering accurate estimation of non-industrial primary sources and secondary sources. This result implies that CMB modelling should not be a straightforward exercise and one have to carefully investigate the marker behaviours and trends beforehand, especially in complex environments such as Marseille. On the other hand, being associated with bursts of submicron particles and carcinogenic and mutagenic components such as PAH, these emissions are most likely related with acute health outcomes and should be regulated despite their small contributions to OC. Another important result is the fact that 78% of OC mass cannot be attributed to the major primary sources and thus remains un-apportioned. We have consequently critically investigated the uncertainties underlying our CMB apportionments. While we have provided some evidence for photochemical decay of hopanes, this decay does not appear to significantly alter the CMB estimates of the total primary OC. Sampling artefacts and unaccounted primary sources also appear to marginally influence the amount of un-apportioned OC. Therefore, this significant amount of un-apportioned OC is mostly attributed to secondary organic carbon that appears to be the major component of OC, during the whole period of study.

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37

Lou, Zhenkai, Fujun Hou, Xuming Lou, and Yubing Zhai. "Tripartite game models in a dual-channel supply chain: competition and cooperation." RAIRO - Operations Research 55, no. 2 (March 2021): 653–71. http://dx.doi.org/10.1051/ro/2021029.

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This paper considers tripartite games in a dual-channel supply chain which involves a manufacturer, an offline retailer and an online retailer. Both competition and cooperation issues are analyzed. In the competition model, a Stackelberg game between the manufacturer and two retailers and a Bertrand game between two retailers occur simultaneously. It is shown that the channel which attracts more consumers’ purchase preference is charged a higher wholesale price and it meanwhile declares a higher sales price. In the presence of revenue sharing, cooperation issues between the three participants are studied and the change of the revenue of each participant is analyzed when partial cooperation exists. Further, the definition of the optimum two-player coalition is proposed. We demonstrate that the channel which attracts more preference of consumers is definitely in the optimum coalition. The structure of the two-player coalition is analyzed. Finally, under revenue sharing and cost apportionments, the change of each participant’s profit is examined.

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He, Xiang, Feng Qian, and Yao Li. "Characterization of Organic Acids with Different Atmospheric Particle Sizes." Advanced Materials Research 599 (November 2012): 14–22. http://dx.doi.org/10.4028/www.scientific.net/amr.599.14.

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Atmospheric particulate samples were collected during January, February, April and May 2012, separately. Twenty-one fatty acids and seven dicarboxylic acids were measured by GC-MS. The results show that average mass concentrations of fatty acids are 809.24ng/m³, 545.34ng/m³, 386.96ng/m³ and dicarboxylic acids are 215.14 ng/m³, 156.45 ng/m³, 111.43 ng/m³ in PM10, PM2.5, PM1, respectively. Fatty acids and dicarboxylic acids concentrate mainly in the PM1. C11-C24 of fatty acids exhibit a significant even carbon predominances, but dicarboxylic acids present no parity preponderance. In the fatty acids, the concentration of hexadecanoic acid is the highest with that of octadecanoic acid followed; Nonandioic acid is the highest in dicarboxylic acids. The results of source apportionments indicate that the fatty acids are mainly related with human activities. Coal burning for heating is the most important source in January and February, but its contribution decreases sharply in April and May for fatty acids; The main source of dicarboxylic acids is photochemical reactions.

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39

Liu, D., J. D. Allan, D. E. Young, H. Coe, D. Beddows, Z. L. Fleming, M. J. Flynn, et al. "Size distribution, mixing state and source apportionments of black carbon aerosols in London during winter time." Atmospheric Chemistry and Physics Discussions 14, no. 11 (June 20, 2014): 16291–349. http://dx.doi.org/10.5194/acpd-14-16291-2014.

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Abstract. Black carbon aerosols (BC) at a London urban site were characterized in both winter and summer time 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorization (PMF) factors of organic aerosol mass spectra measured by a high resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However the size distribution of Dc (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different Dc distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC-AMS-PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), or easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm, and 169 ± 29 nm respectively. The corresponding bulk relative coating thickness of BC (coated particle size / BC core – Dp / Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16, and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10% respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W–SE–E air masses, the BCsf mass fractions ranged from 16 ± 6 %–24 ± 10%–39 ± 14% respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC-AMS-PMF multiple linear regression method (BC-AMS-PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed Absorption Ångström Exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.

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40

Hwang, InJo, and Philip K. Hopke. "Comparison of Source Apportionments of Fine Particulate Matter at Two San Jose Speciation Trends Network Sites." Journal of the Air & Waste Management Association 56, no. 9 (September 2006): 1287–300. http://dx.doi.org/10.1080/10473289.2006.10464586.

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41

Zhang, Jin, Jing Wang, Pei Hua, and Peter Krebs. "The qualitative and quantitative source apportionments of polycyclic aromatic hydrocarbons in size dependent road deposited sediment." Science of The Total Environment 505 (February 2015): 90–101. http://dx.doi.org/10.1016/j.scitotenv.2014.09.091.

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42

Itahashi, Syuichi, Hiroshi Hayami, Keiya Yumimoto, and Itsushi Uno. "Chinese province-scale source apportionments for sulfate aerosol in 2005 evaluated by the tagged tracer method." Environmental Pollution 220 (January 2017): 1366–75. http://dx.doi.org/10.1016/j.envpol.2016.10.098.

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43

Lowenthal, Douglas H., R. Choudary Hanumara, Kenneth A. Rahn, and Lloyd A. Currie. "Effects of systematic error, estimates and uncertainties in chemical mass balance apportionments: Quail Roost II revisited." Atmospheric Environment (1967) 21, no. 3 (January 1987): 501–10. http://dx.doi.org/10.1016/0004-6981(87)90033-3.

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44

Kowalski, Marcin. "Rzymskokatolickie parafie diecezji przemyskiej w dobrach Ordynacji Zamojskiej w połowie XVIII wieku." Studia Archiwalne 6 (2019): 19–44. http://dx.doi.org/10.4467/17347513sa.19.002.14557.

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W artykule przedstawiono dzieje oraz uposażenie czterech parafii wchodzących w skład rzymskokatolickiej diecezji przemyskiej, będących jednocześnie częściami dóbr Ordynacji Zamojskiej, a mianowicie Krzeszowa, Łukowej, Potoku i Tarnogrodu. Do dóbr parafialnych zaliczano ziemię (łany, ogrody, sady, stawy), własne gospodarstwa, pańszczyznę poddanych (wymiarową i tzw. darmochy), dziesięciny i meszne (zbożowe lub pieniężne). Ukazano również podstawy funkcjonowania szpitali i bractw. Agendy te utrzymywały się przeważnie z wypłacanych czynszów oraz niewielkich nadziałów ziemskich. Roman Catholic Parishes of the Przemyśl Diocese in the Zamoyski Entail Estates in the Mid-18th Century The article presents the history and endowment of four parishes that make up the Roman Catholic Diocese of Przemyśl and are at the same time parts of the Zamoyski Entail estates, i.e. Krzeszów, Łukowa, Potok, and Tarnogród. The parish property included land (fields, gardens, orchards, ponds), own farms, corvée of the serfs (specified amount and so-called free service), tithes and poll tax (in grain or money). The study also presents the basis for the functioning of hospitals and fraternities. These institutions usually supported themselves from rents and small land apportionments.

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45

Garcias, Yanina, Romina Torres Astorga, Guillermo Ojeda, Sergio de los Santos Villalobos, Samuel Tejeda, and Hugo Velasco. "Using Geochemical Fingerprints for Assessing Sediment Source Apportionment in an Agricultural Catchment in Central Argentina." Water 13, no. 24 (December 17, 2021): 3632. http://dx.doi.org/10.3390/w13243632.

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In the hilly semi-arid region of central Argentina, where the agricultural frontier expands at the expense of natural ecosystems, soil erosion is one of the most alarming environmental problems. Thus, obtaining knowledge about the dynamics of erosive processes and identifying erosion hotspots constitutes a primary scientific objective. This investigation is focused on estimating the apportionments of main sources of sediments, at the mouth of a small catchment called Durazno del Medio, located in the province of San Luis, Argentina. Elemental Analysis, measured by Energy Dispersive X-ray Fluorescence (EDXRF), was used to select potential geochemical fingerprints of sediment. The unmixing model MixSIAR was applied to approximate the contribution of each identified source in the sediment accumulation areas at the mouth of the catchment. Potential sediment sources were selected using two criteria: (i) a hierarchical approach to identify the main geomorphological units (GUs) and (ii) the main land uses (LU), recognized by examining satellite images and field recognitions. The selected geochemical tracers were able to distinguish sources located in the Crystalline basement hills with loess-patched (CBH) as the main sediment contributors.

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Wang, Jikang, Hailin Gui, Linchang An, Cong Hua, Tianhang Zhang, and Bihui Zhang. "Modeling for the source apportionments of PM10 during sand and dust storms over East Asia in 2020." Atmospheric Environment 267 (December 2021): 118768. http://dx.doi.org/10.1016/j.atmosenv.2021.118768.

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Kang, Yoon-Hee, Seunghee You, Eunhye Kim, Minah Bae, Kyuwon Son, and Soontae Kim. "Local Authority-Level Source Apportionments of PM2.5 Concentrations based on the CAPSS 2016: (VIII) Busan and Gyeongnam." Journal of Korean Society for Atmospheric Environment 37, no. 6 (December 31, 2021): 871–90. http://dx.doi.org/10.5572/kosae.2021.37.6.871.

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48

Yang, Yang, Hailong Wang, Steven J. Smith, Rudong Zhang, Sijia Lou, Hongbin Yu, Can Li, and Philip J. Rasch. "Source Apportionments of Aerosols and Their Direct Radiative Forcing and Long‐Term Trends Over Continental United States." Earth's Future 6, no. 6 (June 2018): 793–808. http://dx.doi.org/10.1029/2018ef000859.

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Cheng, Man-Ting, Wei-Chun Chou, Chia-Pin Chio, Shih-Chieh Hsu, Yi-Ru Su, Pei-Hsuan Kuo, Ben-Jei Tsuang, Shuen-Hsin Lin, and Charles C. K. Chou. "Compositions and source apportionments of atmospheric aerosol during Asian dust storm and local pollution in central Taiwan." Journal of Atmospheric Chemistry 61, no. 2 (October 2008): 155–73. http://dx.doi.org/10.1007/s10874-009-9131-8.

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50

Gao, Xiaomei, Lingxiao Yang, Shuhui Cheng, Rui Gao, Yang Zhou, Likun Xue, Youping Shou, et al. "Semi-continuous measurement of water-soluble ions in PM2.5 in Jinan, China: Temporal variations and source apportionments." Atmospheric Environment 45, no. 33 (October 2011): 6048–56. http://dx.doi.org/10.1016/j.atmosenv.2011.07.041.

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