Kilometers Of Distance Research Articles

Cross-border competition in the gasoline retail market: Impact of proximity at the German-Polish border

In this article, I analyze how persistently lower gasoline prices in Poland affect the prices set in the German border region. Based on a complete dataset of German gasoline prices and an assessment of driving distances between gasoline stations, I estimate the impact of one additional kilometer of distance to the nearest Polish competitor on the price charged by German gasoline stations. Following the fixed effects filtered estimator approach proposed by Pesaran and Zhou (2018) and controlling for various station characteristics, I find no evidence that German gasoline stations enter price competition with their Polish counterparts. My descriptive analysis of gasoline station infrastructure in the German border region reveals increasingly sparse gasoline station density when approaching the Polish border, along with an increasing share of premium brands. These results may reflect the effect of substantially lower taxes in Poland, discouraging German gasoline stations from locating near the border and effectively ruling out cross-border price competition. Although indirect, my findings suggest the presence of fuel tourism.

Energy consumption of a passenger car with a hybrid powertrain in real traffic conditions

The analysis of energy consumption in a hybrid drive system of a passenger car in real road conditions is an important factor determining its operational indicators. The article presents energy consumption analysis of a car equipped with an advanced Plug-in Hybrid Drive System (PHEV), driving in real road conditions on a test section of about 51 km covered in various environmental conditions and seasons. Particular attention was paid to the energy consumption resulting from the cooperation of two independent drive units, analyzed in terms of the total energy expenditure. The energy consumption obtained from fuel and energy collected from the car’s batteries for each run over the total distance of 12,500 km was summarized. The instantaneous values of energy consumption for the hybrid drive per kilometer of distance traveled in car’s real operating conditions range from 0.6 to 1.4 MJ/km, with lower values relating to the vehicle operation only with electric drive. The upper range applies to the internal combustion engine, which increases not only the energy expenditure in the TTW (Tank-to-Wheel) system, but also CO2 emissions to the environment. Based on the experimental data, the curves of total energy consumption per kilometer of the road section traveled were determined, showing a close correlation with the actual operating conditions. Obtained values were compared with homologation data from the WLTP test of the tested passenger car, where the average value of energy demand is 1.1 MJ/km and the CO2 emission is 23 g/km.

Use of Drone to Measure Odour Gases in a Refinery Plant

The objective of this study was to identify odorous gases “fingerprint” and quantify odor throughout the production process of an oil refinery located in Rio Grande do Sul State, Brazil. The NH3 (ammonia), H2S/CH4S (hydrogen sulphide/methylmercaptan), SO2 (sulfur dioxide) and VOCs (volatile organic compounds) gases were measured during 14 consecutive days around emission sources and throughout the company's production process. The monitoring was performed on main stacks, tanks vent, production process and wastewater treatment station. To measure over the stacks, it was used a Drone DJI to suspend a set of integrated electrochemical sensors that analyze the air continuously. This system made it possible to record the emission from stacks at heights of up to 120 meters above ground level, which was previously impossible to accomplish. Cairpol’s electrochemical sensors were used to provide automatic and continuous measurement. This equipment records the measurements in ppb (part per billion) every minute and stores them in an internal data logger. The odorous gas analysis results showed that the largest sources of emissions are the industrial effluent treatment, which is responsible for the emission H2S/CH4S and VOCs and the emission from the oil-water separator is only of VOCs. The flare stack and the Sulfur Recovery Unit’s stack are the main emitters of H2S/CH4S and SO2. However, the coverage radius for the effluent treatment station and the oil-water separator is small due to the emission characteristics, as the emissions at ground level. The main sources of odor emission that can spread and annoy the neighborhood are the stacks as they presented the higher concentrations, henceforth their odor emission can be perceived from kilometers of distance.

A data-driven pipeline pressure procedure for remote monitoring of centrifugal pumps

Pumping systems are a key component of oil and gas pipeline transportation assets: monitoring their integrity is a crucial operation from a safety and revenue point of view. The solutions currently employed in the industry apply supervised machine learning techniques to data collected by multi-domain sensors directly installed on several positions of the pump itself; however, such approaches are not applicable on older machines, in contexts where a direct access to the pump is not possible, or whenever labelled data are not at disposal. This paper, instead, presents a predictive maintenance strategy where the condition of a centrifugal pump is tracked by solely exploiting standard pressure measurements, recorded also on remote points along the pipeline, and using an unsupervised learning approach. The smart monitoring strategy is presented and validated on historical pressure signals collected by Eni for several years on a crude oil transportation pipeline, located in Italy. Pressure data, recorded along the fluid line, are used to compute several statistical indicators on appropriate window lengths. These indicators are then fed to an unsupervised clustering procedure, based on a Gaussian mixture model. The output is an index within four different pump operational regimes, and a clustering visualization that permits the interpretation of the automatic regime classification. In fact, the manual inspection of the clusters shows that three of them describe standard modes (regular pumping operation, pumps off, flow regulations). The fourth one corresponds to high amplitude peaks in the signals and indicators, and so it is tagged as “anomalous” mode: pump maintenance logs reveal that the peaks are associated to damaged roller bearing movements, which disappear after the activation of the pump backup system. Anomalies are reported several days before the pump switch, so that a preventive maintenance could have been triggered. The robustness of the clustering algorithm is assessed on a statistical basis, whereas the overall validity of the monitoring system is tested on an instantaneous basis by applying the proposed model on two independent datasets, collected on real transportation pipelines: the results demonstrate the reliability of the proposed monitoring strategy in predicting and detecting all the pump failure events reported by the available maintenance logs. With respect to the mostly employed approaches, our machine learning procedure does not require any previous supervision of the data. Moreover, input data are the pressure transients produced by the pumps and guided within the fluid in the pipeline for long distances: pump failure analysis can be run using sensors located at several kilometers of distance from the pump itself, making a remote control strategy feasible.

RTK-LoRa: High-Precision, Long-Range, and Energy-Efficient Localization for Mobile IoT Devices

High-precision global navigation satellite system (GNSS) is a crucial geolocalization feature enabling a wide range of applications, from mobile Internet-of-Things devices to autonomous drones and self-driving vehicles. Real-time kinematic (RTK) is a GNSS technology that attracting increased interest due to the centimeter precision achievable when wireless communication is present on the devices. On the other hand, sending continuously wireless data increases the energy consumption and the cost of the solution, especially when communication is carried over the 4G network. Due to those drawbacks, RTK is not much exploited in the localization of battery-operated devices. This work combines RTK with low-power long-range communication to achieve submeter precision in an energy-efficient RTK-based system. The proposed system exploits a state-of-the-art RTK-GNSS module combined with a long range (LoRa) to achieve geolocalization with minimal wireless radio infrastructure requirements. An energy-efficient algorithm is proposed and implemented in a microcontroller to have a quick startup and high accuracy. We evaluate three different GNSS modules and compare their performance in terms of power and accuracy. Experimental results, with in-field measurements, show that an average geolocalization precision of tens of centimeters is achievable on a battery-operated wireless end node connected to a single base station used as a geostationary reference anchor placed at kilometers of distance. The peak precision measured is below 10 cm.

Predictive variables for hemodialysis and death in Japanese spotted fever, and the association between distance from rivers and incidence

The number of patients with Japanese spotted fever (JSF) and its case fatality rate have been increasing in Japan and other East Asian countries. Better clinical and laboratory biomarkers are needed to avoid misdiagnosing JSF and to predict severe cases. In addition to determining these predictors, we aimed to examine the association between the incidence of JSF and the distance from rivers, in Hiroshima Prefecture, one of the most JSF prevalent areas in Japan. Patients diagnosed with JSF from 2009 to 2017 in two hospitals in Onomichi City in Hiroshima Prefecture were studied, and their clinical characteristics and laboratory data were collected retrospectively from medical charts. A random forest was used to identify predictors of severe JSF leading to hemodialysis or death. A multivariable negative binomial regression model was utilized to analyze the association between the cumulative incidence in each postal code area and the distance from the residential postal code area to the closest river. Out of 82 patients with JSF (mean age at diagnosis, 74.1 ± 10.6 years; 34 (41.5 %) men), 6 cases were regarded as severe (among them 5 hemodialysis patients and 3 deaths). Twenty-eight (34.1 %) patients were misdiagnosed at least once at the initial hospital visit. Laboratory examination showed 34.5 % had atypical lymphocytes, 73.8 % had no eosinophils, 75.6 % had an elevated aspartate aminotransferase (AST) level, and 69.5 % had hyponatremia. Among cases without urine leucocytes, 63.3 % had proteinuria and 63.3 % had hematuria. Low serum total protein was the strongest predictor of severe JSF, followed by high blood urea nitrogen (BUN) and low albumin. Geospatial analysis showed a significant negative association between the cumulative incidence of JSF cases and the distance from rivers in an adjusted model: the cumulative incidence decreased by 0.51 times (95 % CI: 0.30 to 0.86) for every kilometer of distance from the residential postal code area to the closest river. Some laboratory data may be useful in averting misdiagnosis of JSF and in predicting severe cases. Additional studies should be done in order to clarify the mechanism and association of the incidence of JSF with the distance from the nearest river.

The impact of climate change on the Australian sugarcane industry

Abstract This study assesses the impact of climate change on changes in sugarcane output for Australia’s main sugarcane-growing regions, using a dataset for the years 1964–2012. We test for accelerated effects of climate change post-1995 (the midpoint in our testing period), as well as for possible non-linear impacts of climate change that are related to the geographical location of sugarcane plantations. Our findings show that increases in atmospheric carbon concentration have had a significant negative impact on sugarcane output after 1995, which contrasts with an earlier positive effect before 1995. Peak temperatures also had a larger impact on sugarcane output after 1995. For areas south of the tropical line and from 1995 onwards, an extra kilometer of distance from the tropical line corresponds to an increase of 1 million tons in sugarcane output growth. Our study tests for additional variables (irrigation, sugarcane diseases, fertilizer use, and dominant sugarcane variety planted) with results remaining similar. We conclude by discussing implications for policymakers and future research, in particular, the importance of factoring in regional differences and non-linear effects into adaptation planning across agricultural regions.

Does urban vegetation reduce temperature and air pollution concentrations? Findings from an environmental monitoring study of the Central Experimental Farm in Ottawa, Canada

Urban greenness, or vegetation, plays an important role in reducing ambient air pollution and urban heat island temperatures. While several studies have developed land use regression surfaces to describe the intra-urban variability of these environmental exposures, it is less well known how green spaces modify these surfaces. In this study, we investigated these environmental benefits of green spaces for the Canadian Central Experimental Farm, a 4 km2 agricultural facility, located adjacent to the urban core of Ottawa, Canada. Fall, winter and summer mobile monitoring campaigns were conducted in 2016/17 within a 40 km2 area centered on the CEF to characterize the spatial variability of: fine particulate matter (PM2.5), ultrafine particles (UFPs), black carbon (BC) and temperature. We concurrently measured two routes each morning (09:30-10:30) and evening (17:00-18:00) for 14 consecutive days in the three seasons. Median exposure levels for each road segment were calculated and used as inputs for season-specific land use regression models. These models were developed for each combination of environmental variable (PM2.5, UFP, BC, and temperature) and season (fall, winter, and summer). Predictors included land and road types as well as season-specific urban greenness represented by the Normalized Difference Vegetation Index (NDVI). Levels and spatial patterns of air pollution and temperature varied by season. We characterized the spatial relationship between the CEF and ambient air pollution and temperature measures by developing linear regression models with the distance to the closest border of the farm as the main predictor. Other land use variable which changed the main effect by ≥ 10% were included in the models. Within the study area, each kilometer of distance from the closest CEF border was associated with increases of fall PM2.5 (12.1%, 95%CI: 6.1%–18.4%), winter PM2.5 (6.8%, 95%CI: 2.4%–11.3%), summer BC (74.1%, 95%CI: 12.2%–167.7%), and fall temperature (2.8%, 95%CI: 1.3%–4.2%). These results suggest that this unique urban green space has important beneficial impacts on ambient air pollution concentrations and for mitigating extreme heat events for which a large portion of Ottawa's populace is exposed.

On-Demand LoRa: Asynchronous TDMA for Energy Efficient and Low Latency Communication in IoT.

Energy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance. Low-power and long-range communication technologies such as LoRaWAN are becoming popular in IoT applications. However, LoRaWAN has drawbacks in terms of (i) data latency; (ii) limited control over the end devices by the gateway; and (iii) high rate of packet collisions in a dense network. To overcome these drawbacks, we present an energy-efficient network architecture and a high-efficiency on-demand time-division multiple access (TDMA) communication protocol for IoT improving both the energy efficiency and the latency of standard LoRa networks. We combine the capabilities of short-range wake-up radios to achieve ultra-low power states and asynchronous communication together with the long-range connectivity of LoRa. The proposed approach still works with the standard LoRa protocol, but improves performance with an on-demand TDMA. Thanks to the proposed network and protocol, we achieve a packet delivery ratio of 100% by eliminating the possibility of packet collisions. The network also achieves a round-trip latency on the order of milliseconds with sensing devices dissipating less than 46 mJ when active and 1.83 W during periods of inactivity and can last up to three years on a 1200-mAh lithium polymer battery.

Spatial differences in the accumulation of elements by the lichen Cladonia rangiferina L. in the Pasvik Nature Reserve

Nature Reserve and its surroundings (the Murmansk Region). The most significant factor influencing the accumulation of elements is the distance to non-ferrous metal industry facilities (industrial sites of the Kola Mining and Metallurgic Company (Kola MMC) of the Norilsk Nickel Holding). The exponential function proved to be well fit for this dependence. The elements fall into two groups: 1) elements present in the plant’s emissions and having a pronounced spatial gradient in the nature reserve and its surroundings (Cr, Fe, Co, Cu, Ni, Cd, Pb, As), and 2) elements which have no clear patterns in the distribution and depend on the “background” values (Zn, Mn and Hg). The concentrations of group 1 pollutants in the lichen decreased at a rate of 2–5 % for each kilometer of distance from the source of emissions. The content of most of the elements significantly (p < 0.05) correlated with each other. The exception was Mn, whose content was inhibited by an increase in the concentrations of other metals (primarily Pb, Fe, Co). Even samples with the lowest Ni, Cu, Co and Cd content from the sites furthest away from the source in the Pasvik Reserve and its surroundings had the elements concentrations higher than the environmental ‘background’ for adjacent tundra communities (Kanin tundra, Nenets Autonomous District). Lichens of the Pasvik Reserve accumulate higher concentrations of the main pollutants (Ni, Cu, Co and Fe) than vascular plants in the same territory. Graphic isopleths of the distribution of potential contaminant concentrations in lichen thalli were plotted for the territory of the reserve. The Pasvik Nature Reserve was used as the example to demonstrate that, at present, ecosystem components within protected areas cannot be regarded as geochemical standards for the regional environment due the regional atmospheric transfers from nearby industrial facilities.

Risk Factors for Mortality in Children Hospitalized with Severe Malaria in Northern Zambia: A Retrospective Case-Control Study.

.Malaria remains a public health crisis in areas where it has resisted control efforts. In Nchelenge District, a high-transmission area in northern Zambia, malaria accounts for more than one-third of pediatric hospitalizations and nearly one-half of hospital deaths in children. To identify risk factors for death due to malaria, we conducted a retrospective, time-matched case-control study of 126 children hospitalized with malaria who died (cases) and 126 children who survived (controls). There were no differences in age, gender, hemoglobin concentration, or prevalence of severe anemia between cases and controls. Children who died were more likely to come from villages located at greater distances from the hospital than children who survived (median 13.5 versus 3.2 km). Each additional kilometer of distance from the hospital increased the odds of death by 4% (odds ratio 1.04, 95% confidence interval 1.01–1.07, P < 0.01). Extent of anemia and admission during periods when blood was unavailable for transfusion were associated with early death (P ≤ 0.03). Delays in initiation of treatment of severe malaria contribute to the increased odds of death in children referred from more distant health centers, and might be mitigated by transportation improvements, capacity at rural health posts to administer treatment before transfer, hospital triage systems that minimize time to treatment, and reliable blood product stores at referral hospitals.

Biogeographic Events Are Not Correlated with Diaspore Dispersal Modes in Boraginaceae

Long-distance dispersal seems to be the main biogeographic event responsible for intriguing distribution patterns in plant groups in which sister taxa are separated by thousands of kilometers of distance across oceans and continents. The biotic and abiotic mechanisms behind such dispersal events are poorly understood and many attempts have been made to explain how plants can manage to disperse and survive these long journeys. The biogeographic history of Boraginaceae, a subcosmopolitan plant family with many disjunct clades, is here addressed and analyzed in the context of the different dispersal modes exhibited by the species. The lack of a clear pattern between the main dispersal events in Boraginaceae and the phylogenetic distribution of the dispersal modes indicates that no single dispersal mechanism can be associated with the events of dispersal in the family. Moreover, adaptations to different dispersal agents and unassisted dispersal modes in some clades might have promoted the diversification of Boraginaceae in various habitats across several continents. Our study reveals that long-distance dispersal is a very complex process that needs to be analyzed in the context of climatic and environmental changes and the response of plants and their dispersal vectors to these variable conditions.

Factors Associated with Time to Arrival at a Regional Pediatric Trauma Center.

The goal of this study was to test the hypothesis that the prehospital time between injury and arrival at a trauma center for critically injured children is associated with patient injury severity and mode of transport. Secondary analysis of prospectively collected data on children 0-17 years of age admitted with traumatic injuries to a designated Level I pediatric trauma center from January 1, 2006 through September 30, 2007 was conducted. Multivariate regression methods were used to assess for factors independently associated with prehospital time. Of 1,175 admissions during the study period, only 355 (30%) had a prehospital time within 60 minutes of injury. Prehospital time within 60 minutes of injury was associated with higher frequency of coma, higher mean injury severity scores (ISS), and greater frequency of admission to the intensive care unit when compared with prehospital time beyond 60 minutes of injury. Children who arrived at the trauma center within 60 minutes versus beyond 60 minutes were 13-fold (odds ratio [OR]: 12.9; 95% Confidence Interval [CI], 7.6-22.0) more likely to be transported via air ambulance than a private vehicle, and had 4.8-fold greater odds (95% CI, 2.2-10.3) of transport via ground ambulance than private vehicle. For each kilometer of distance between the injury zip code and the trauma center, the odds of arrival within 60 minutes versus beyond 60 minutes decreased by 15% (OR: 0.85; 95% CI, 0.79-0.91). Field triage and decision making appeared to correlate with severity of patient injury with expeditious transport of the most severely injured children to definitive trauma care. This finding serves as important groundwork that might enable further study into factors that influence triage and overall prehospital care for critically injured children.

Functional chart of a multichannel hydrologic-optical-chemical measuring complex and new measuring channels of hydrophysical parameters

The results of the analysis of design and development of data measuring systems of oceanographic parameters in the 60-70s and 80-90s are presented in the paper. Data measuring systems based on the CAMAC standard (created under the leadership of academician Nesterikhin Y.E.) had a great influence on the design of instrumentation. However, their direct use in oceanographic measurements proved impossible. It so happened because of the need for in situ measurement of parameters at a considerable distance from the control devices. A basic structural arangement of a measurement system was developed by the end of the 80s and oceanographic sounding towed autonomous measuring systems were created, certified and put into practice. They were used for experimental studies in the ocean in the range from seconds to tens of days in time and from centimeters to hundreds or thousands of kilometers in distance. Measuring channels are being developed on the basis of high-speed data receivers (television cameras, acoustic devices). A structural arrangement of a multi-channel hydrological- optical- and chemical measuring complex that makes it possible to assimilate in its composition measuring channels of oceanographic parameters at different information rates has been developed. A process platform for the development, testing and certification of new measurement channels for the parameters of the marine environment has been designed and built on the basis of this scheme. The results of full-scale tests of the process platform carried out on the Black Sea near Gelendzhik are presented.

Real-time pose estimation of a dynamic quadruped in GPS-denied environments for 24-hour operation

We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate six-degree-of-freedom pose estimate (within a 1.0% error of distance traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external disturbances, such as slips or falls. The system fuses a stereo-camera sensor, inertial measurement unit, leg odometry, and optional intermittent GPS position updates with an extended Kalman filter to ensure robust, low-latency performance. To maintain a six-degree-of-freedom local positioning accuracy alongside the global positioning knowledge, two reference frames are used; a local reference frame and a global reference frame, with the former benefiting obstacle detection and mapping and the latter for operator-specified and autonomous way-point following. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs and hundreds of kilometers of distance traveled in a wide variety of terrains and conditions.

In Pakistan, Poor and Rural Women Must Travel Farther To Give Birth in a Facility

Poor and rural women in Pakistan are disadvantaged in terms of their access to institutional services, according to a geographic analysis of data from nine districts. (1) On average, married women who reported giving birth within the past three years lived seven kilometers by road from the nearest health facility offering care; the average distance ranged from five kilometers among the wealthiest women to 10 kilometers among the poorest. Women's odds of delivering in a facility decreased by 3% per additional kilometer of distance from the nearest facility, although this association held only in rural areas. Living within 10 kilometers of a facility offering or emergency obstetric was positively associated with institutional (odds ratios, 1.8 and 1.7, respectively). To examine relationships between geographic and economic access to a health facility and institutional delivery, researchers linked survey data for individual women and health facilities in study districts with data on distance between the primary sampling unit of women's residence and health facilities in those districts. The individual data were drawn from a 2005 survey that asked married women in selected households in primary sampling units about their health before, during and after delivery, as well as about their social and demographic characteristics. Household wealth was measured in quartiles (lowest, lower middle, upper middle and highest) on the basis of such criteria as ownership of certain household amenities and types of construction materials used for the household's dwelling. The sample of women was restricted to the 4,435 women who reported giving birth in the past three years. Facility data were drawn from a 2008 survey of all health facilities, ranging from large public teaching and district hospitals to private registered clinics and community pharmacies. A structured questionnaire was used to ask individuals in charge of facilities about the type and level of available reproductive health care; it included questions about staff, equipment and client amenities. The sample included all 763 facilities that offered obstetric services before 2005. Of those, 547 were considered able to provide only normal delivery (i.e., assisted vaginal in a health facility that lacked an operating room), 91 could also provide basic emergency obstetric care (assisted deliveries, manual extraction of the placenta and removal of retained products) and 125 could further provide comprehensive emergency obstetric care (cesarean sections and blood transfusions). In addition, as part of the individual and health facility surveys, the exact locations of primary sampling units and facilities were determined using global positioning system (GPS) devices. The researchers used the GPS data to create georeferenced digital maps that included health facilities, district and subdistrict boundaries, rivers and roads, and then used global information system software to calculate exact road distances between prima ry sampling units and health facilities within each district. Two measures of geographic access to services were created: the distance from each primary sampling unit to the nearest health facility, and the highest level of within 10 kilometers of each primary sampling unit. Multilevel mixed-effects logistic regression analyses were conducted to examine associations between geographic access, wealth status and institutional delivery. Most women (84%) lived in a rural area; 20% lived in households in the lowest wealth quartile, 24% in the lower middle, 27% in the upper middle and 29% in the highest. …

UN interventions: The role of geography

This paper argues that UN military interventions are geographically biased. For every 1,000 kilometers of distance from the three permanent Western UNSC members (France, UK, US), the probability of a UN military intervention decreases by 4 percent. We are able to rule out several alternative explanations for the distance finding, such as differences by continent, colonial origin, bilateral trade relationships, foreign aid flows, political regime forms, or the characteristics of the Cold War. We do not observe this geographical bias for non-military interventions, providing evidence that practical considerations could be important factors for UNSC decisions to intervene militarily. In fact, UNSC interventions are also more likely in smaller and poorer countries – both of which are indications of less costly interventions and higher chances of success, everything else equal.

The Determinants of UN Interventions - Are There Regional Preferences?

What leads the United Nations Security Council to intervene in one conflict, but remain inactive in others of similar magnitude and cruelty? This paper analyzes all registered 178 internal and internationalized internal conflicts since 1945, with the goal to unveil what determines the probability of a UN intervention. Our main focus lies on the question whether the geographical proximity to the ve permanent members of the UN Security Council (China,France, Russia, the United Kingdom, and the United States) has an e ect on the probability of intervention. Our results suggest that the UN is substantially more likely to intervene in conflicts located in Europe. A more detailed look at distances revels that for every 1,000 kilometers of distance from France or the United Kingdom the probability of intervention decreases by about one third. Further, we nd that UN intervention is signi cantly more likely to happen in smaller (less population), poorer (smaller GDP per capita), and less open economies (openness to international trade).

The Determinants of Un Interventions -- Are There Regional Preferences?

What leads the United Nations Security Council to intervene in one conflict, but remain inactive in others of similar magnitude and cruelty? This paper analyzes all registered 178 internal and internationalized internal conflicts since 1945, with the goal to unveil what determines the probability of a UN intervention. Our main focus lies on the question whether the geographical proximity to the ve permanent members of the UN Security Council (China,France, Russia, the United Kingdom, and the United States) has an e ect on the probability of intervention. Our results suggest that the UN is substantially more likely to intervene in conflicts located in Europe. A more detailed look at distances revels that for every 1,000 kilometers of distance from France or the United Kingdom the probability of intervention decreases by about one third. Further, we nd that UN intervention is signi cantly more likely to happen in smaller (less population), poorer (smaller GDP per capita), and less open economies (openness to international trade).

Assessing spatial and temporal variability of VOCs and PM-components in outdoor air during the Detroit Exposure and Aerosol Research Study (DEARS)

Exposure models for air pollutants often adjust for effects of the physical environment (e.g., season, urban vs. rural populations) in order to improve exposure and risk predictions. Yet attempts are seldom made to attribute variability in observed outdoor air measurements to specific environmental variables. This research presents a statistical strategy to identify and explain the spatial and temporal components of air pollutant measurement variance using regional predictors and large-scale (with impacts over multiple kilometers of distance) emission source effects. The emission sources considered in this investigation include major highways and industries, and were chosen based on their proximity to monitoring areas designated in the Detroit Exposure and Aerosol Research Study (DEARS). Linear mixed effects models were used to investigate 24-h averaged outdoor residential air measurements of several pollutants, including PM2.5 mass, PM components (elemental carbon, organic carbon, metals, elements), nitrogen dioxide, and volatile organic compounds (VOCs). Three hierarchal statistical models were utilized to calculate and examine variance component estimates for each analyte before and after adjustment for fixed effects, which included sampling season, day of the week, air concentrations at an ambient (centralized) monitoring site, and the frequency of time a receptor was downwind of specific large-emissions sources. Results indicate that temporal variability accounted for the majority of total measurement variance (90% on average). Adjustments for ambient concentration and sampling season significantly reduced temporal variance estimates for most VOCs and for about half of the PM components (generally with reductions of 24–97%). Major exceptions to this trend were found with metals (Fe, Mn, and Zn), ethyltoluene, and p-dichlorobenzene, where only 4–30% of the temporal variance was explained after the same adjustments. Additional reductions in temporal variance (up to 37%) were observed after adjusting for the large-emission sources and day of the week effects, with the strongest effects observed for PM components, including select metals. Thus, for the Detroit airshed, VOCs appear to have been largely affected by regional factors, whereas PM components were explained by both regional factors and localized large-emissions sources. Examination of the radial directions associated with suspected emission sources generally supported a priori expectations of source–analyte associations (e.g., NO2 increases from areas of high vehicle traffic). Overall, this investigation presents a statistical multi-pollutant analysis strategy that is useful for simultaneously (1) estimating spatial and temporal variance components of outdoor air pollutant measurements, (2) estimating the effects of regional variables on pollutant levels, and (3) identifying likely emissions sources that may affect outdoor air levels of individual or co-occurring pollutants.