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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Development of fiber orientation in injection molding: Comparison of glass fiber, carbon fiber and their hybrid composites

Fiber orientation distribution (FOD) in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for glass fiber (GF), carbon fiber (CF), and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varied with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of impurity driven corrosion behavior in molten 2LiF-BeF 2 salt

A 1000 -h corrosion experiment of 316H stainless steel at 700 °C investigated the role of metal fluoride impurities CrF 2 and FeF 2 in LiF-BeF 2 (66-34 mole %) (FLiBe) salt. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) demonstrated the ability to measure changes in the concentration of these fluorides in FLiBe salt. Cyclic voltammetry (CV) showed the potential for real-time quantitative concentration measurement of corrosion products in the molten salt. Materials characterization revealed that both impurity species influence the dissolution of Cr from the alloy. The collective results from these analysis methods advance the understanding of the influence impurities have on materials corrosion.

2LiF-BeF2↗
DOE OSTI2021

Safety and effectiveness of a non-electric infant warmer for hypothermia in Rwanda: A cluster-randomized stepped-wedge trial

Background: Neonatal hypothermia is a common source of morbidity and mortality in low resource settings. We developed the Dream Warmer, a low cost, re-usable non-electric infant warmer to prevent and treat hypothermia. Methods: We conducted a cluster-randomized stepped-wedge trial. The primary aim was to assess the effect on overall euthermia rates of introducing the warmer compared to standard of care in rural Rwandan hospitals. The secondary aims were to assess effects of warmer introduction on mortality, as well as the safety and feasibility of the warmer. Ten district hospitals participated in the study from November 19th 2019 to July 15th 2020. Patients were eligible to use the warmer if they were 1) hypothermic (temp < 36·5 °C) or 2) or at risk of hypothermia (weight < 2·5 kg or estimated post menstrual age < 35 weeks) when Kangaroo Mother Care was not available. An encounter was defined as the data from an individual infant on a single day. Trial of a Non Electric Infant Warmer for Prevention and Treatment of Hypothermia in Rwanda [NCT03890211]. Findings: Over the study period, 3179 patients were enrolled across the ten neonatal wards, yielding 12,748 encounters; 464 unique infants used the warmer 892 times, 79% eligible due to hypothermia. Because of limited study nurse resources, the warmer was used in only 18% of eligible encounters. Despite this low rate of warmer use, the rate of euthermia rose from 51% (95% CI 50–52%) of encounters pre-intervention to 67% (66–68%) post-intervention; p < 0·0001. Among the encounters in which the warmer was used, only 11% (9–13%) remained hypothermic. While mortality rates pre- and post-intervention did not change, mortality rate among those who used the warmer was significantly lower than among those who did not (0·9% vs 2·8%, p = 0·01). Use of the warmer did not affect hyperthermia rates. There were no safety concerns or instances of incorrect warmer use. Interpretation: Introduction of the warmer increased rates of euthermia with no associated safety concerns.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗
DOE OSTI2023

Probabilistic feasibility assessment of sequestration reliance for climate targets

Countries worldwide are transforming their energy systems to achieve Carbon-Neutrality. Investing in renewable resources-based technologies and implementing Carbon Capture and Storage (CCS) are common strategies to achieve higher sequestration levels. Negative emissions through Bioenergy with CCS are expected to play an essential role in the transition to full decarbonization. On top of that, biomass is a limited resource that depends on environmental factors, which create uncertainties related to the amount that can be sustainably provided to the energy system. Here this study emphasizes the relevance of variability in carbon sequestration for achieving climate targets by 2050. Here this paper proposes a probabilistic approach that integrates the Global Change Analysis Model for Latin America (GCAM-LA) with a chance constraint approach. GCAM-LA is used to assess the impact on the energy sector of different limits of sustainable biomass and carbon budget scenarios. The risk associated with exceeding the sequestration capacity of a given region is modeled via Chance Constraint. Results show that electrification is an appropriate long-term decarbonization strategy. It smoothes the effects of uncertainty in sequestration capacity and responds to end-user demands. For this case study, higher levels of electrification are obtained at likelihood levels >66% for end-use sectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Energy use and CO2 emissions of China’s industrial sector from a global perspective

The industrial sector has accounted for more than 50% of China’s final energy consumption in the past 30 years. Understanding the future emissions and emissions mitigation opportunities depends on proper characterization of the present-day industrial energy use, as well as industrial demand drivers and technological opportunities in the future. Traditionally, however, integrated assessment research has handled the industrial sector of China in a highly aggregate form. In this study, we develop a technologically detailed, service-oriented representation of 11 industrial subsectors in China, and analyze a suite of scenarios of future industrial demand growth. We find that, due to anticipated saturation of China’s per-capita demands of basic industrial goods, industrial energy demand and CO2 emissions approach a plateau between 2030 and 2040, then decrease gradually. Still, without emissions mitigation policies, the industrial sector remains heavily reliant on coal, and therefore emissions-intensive. With carbon prices, we observe some degree of industrial sector electrification, deployment of CCS at large industrial point sources of CO2 emissions at low carbon prices, an increase in the share of CHP systems at industrial facilities. These technological responses amount to reductions of industrial emissions (including indirect emission from electricity) are of 24% in 2050 and 66% in 2095.

China↗
DOE OSTI2020

Microbial functional genes commonly respond to elevated carbon dioxide

Atmospheric CO 2 concentration is increasing, largely due to anthropogenic activities. Previous studies of individual free-air CO 2 enrichment (FACE) experimental sites have shown significant impacts of elevated CO 2 (eCO 2 ) on soil microbial communities; however, no common microbial response patterns have yet emerged, challenging our ability to predict ecosystem functioning and sustainability in the future eCO 2 environment. Here we analyzed 66 soil microbial communities from five FACE sites, and showed common microbial response patterns to eCO 2 , especially for key functional genes involved in carbon and nitrogen fixation (e.g., pcc/acc for carbon fixation, nifH for nitrogen fixation), carbon decomposition (e.g., amyA and pulA for labile carbon decomposition, mnp and lcc for recalcitrant carbon decomposition), and greenhouse gas emissions (e.g., mcrA for methane production, norB for nitrous oxide production) across five FACE sites. Also, the relative abundance of those key genes was generally increased and directionally associated with increased biomass, soil carbon decomposition, and soil moisture. In addition, a further literature survey of more disparate FACE experimental sites indicated increased biomass, soil carbon decay, nitrogen fixation, methane and nitrous oxide emissions, plant and soil carbon and nitrogen under eCO 2 . A conceptual framework was developed to link commonly responsive functional genes with ecosystem processes, such as pcc/acc vs. soil carbon storage, amyA/pulA/mnp/lcc vs. soil carbon decomposition, and nifH vs. nitrogen availability, suggesting that such common responses of microbial functional genes may have the potential to predict ecosystem functioning and sustainability in the future eCO 2 environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Manganese: The overlooked contaminant in the world largest mine tailings dam collapse

Manganese (Mn) is an abundant element in terrestrial and coastal ecosystems and an essential micronutrient in the metabolic processes of plants and animals. Mn is generally not considered a potentially toxic element due to its low content in both soil and water. However, in coastal ecosystems, the Mn dynamic (commonly associated with the Fe cycle) is mostly controlled by redox processes. Here, we assessed the potential contamination of the Rio Doce estuary (SE Brazil) by Mn after the world’s largest mine tailings dam collapse, potentially resulting in chronic exposure to local wildlife and humans. Estuarine soils, water, and fish were collected and analyzed seven days after the arrival of the tailings in 2015 and again two years after the dam collapse in 2017. Using a suite of solid-phase analyses including X-ray absorption spectroscopy and sequential extractions, our results indicated that a large quantity of Mn II arrived in the estuary in 2015 bound to Fe oxyhydroxides. Over time, dissolved Mn and Fe were released from soils when Fe III oxyhydroxides underwent reductive dissolution. Due to seasonal redox oscillations, both Fe and Mn were then re-oxidized to Fe III , Mn III , and Mn IV and re-precipitated as poorly crystalline Fe oxyhydroxides and poorly crystalline Mn oxides. In 2017, redox conditions (Eh: -47 ± 83 mV; pH: 6.7 ± 0.5) favorable to both Fe and Mn reduction led to an increase (~880%) of dissolved Mn (average for 2015: 66 ± 130 μg L -1 ; 2017: 582 ± 626 μg L -1 ) in water and a decrease (~75%, 2015: 547 ± 498 mg kg -1 ; 2017: 135 ± 80 mg kg -1 ) in the total Mn content in soils. The crystalline Fe oxyhydroxides content significantly decreased while the fraction of poorly ordered Fe oxides increased in the soils limiting the role of Fe in Mn retention. The high concentration of dissolved Mn found within the estuary two years after the arrival of mine tailings indicates a possible chronic contamination scenario, which is supported by the high levels of Mn in two species of fish living in the estuary. Our work suggests a high risk to estuarine biota and human health due to the rapid Fe and Mn biogeochemical dynamic within the impacted estuary.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Incidence of non-lung solid cancers in Czech uranium miners: A case-cohort study

Objectives: Uranium miners are chronically exposed to radon and its progeny, which are known to cause lung cancer and may be associated with leukemia. This study was undertaken to evaluate risk of non-lung solid cancers among uranium miners in Pribram region, Czech Republic. Methods: A retrospective stratified case-cohort study in a cohort of 22,816 underground miners who were employed between 1949 and 1975. All incident non-lung solid cancers were ascertained among miners who worked underground for at least 12 months (n=1020). A subcohort of 1707 subjects was randomly drawn from the same population by random sampling stratified on age. The follow-up period lasted from 1977 to 1996. Results: Relative risks comparing 180 WLM (90th percentile) of cumulative lifetime radon exposure to 3 WLM (10th percentile) were 0.88 for all non-lung solid cancers combined (95% CI 0.73-1.04, n=1020), 0.87 for all digestive cancers (95% CI 0.69-1.09, n=561), 2.39 for gallbladder cancer (95% CI 0.52-10.98, n=13), 0.79 for larynx cancer (95% CI 0.38-1.64, n=62), 2.92 for malignant melanoma (95% CI 0.91-9.42, n=23), 0.84 for bladder cancer (95% CI 0.43-1.65, n=73), and 1.13 for kidney cancer (95% CI 0.62-2.04, n=66). No cancer type was significantly associated with radon exposure; only malignant melanoma and gallbladder cancer showed elevated but non-significant association with radon. Conclusions: Radon was not significantly associated with incidence of any cancer of interest, although a positive association of radon with malignant melanoma and gallbladder cancer cannot be entirely ruled out. - Research highlights: {yields} Uranium miners are chronically exposed to radon. {yields} We evaluate risk of non-lung solid cancers among uranium miners. {yields} No cancer type was significantly associated with radon exposure. {yields} Malignant melanoma and gallbladder cancer showed non-significant elevated risk.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Residential radon exposure and risk of incident hematologic malignancies in the Cancer Prevention Study-II Nutrition Cohort

Dosimetric models show that radon, an established cause of lung cancer, delivers a non-negligible dose of alpha radiation to the bone marrow, as well as to lymphocytes in the tracheobronchial epithelium, and therefore could be related to risk of hematologic cancers. Studies of radon and hematologic cancer risk, however, have produced inconsistent results. To date there is no published prospective, population-based study of residential radon exposure and hematologic malignancy incidence. We used data from the American Cancer Society Cancer Prevention Study-II Nutrition Cohort established in 1992, to examine the association between county-level residential radon exposure and risk of hematologic cancer. The analytic cohort included 140,652 participants (66,572 men, 74,080 women) among which 3019 incident hematologic cancer cases (1711 men, 1308 women) were identified during 19 years of follow-up. Cox proportional hazard regression was used to calculate multivariable-adjusted hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for radon exposure and hematologic cancer risk. Women living in counties with the highest mean radon concentrations (>148 Bq/m{sup 3}) had a statistically significant higher risk of hematologic cancer compared to those living in counties with the lowest (<74 Bq/m{sup 3}) radon levels (HR=1.63, 95% CI:1.23–2.18), and there was evidence of a dose-response relationship (HR{sub continuous}=1.38, 95% CI:1.15–1.65 per 100 Bq/m{sup 3}; p-trend=0.001). There was no association between county-level radon and hematologic cancer risk among men. The findings of this large, prospective study suggest residential radon may be a risk factor for lymphoid malignancies among women. Further study is needed to confirm these findings. - Highlights: • This is the first prospective, general population study of residential radon and risk of hematologic cancer. • Findings from this study suggest that residential radon exposure may be a risk factor for lymphoid malignancies. • The biologic mechanism for the association between radon exposure and lymphoma risk may be different than for lung cancer. • Confirmation of this association would warrant strengthened public health efforts to mitigate residential radon risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Occurrence of cyclic imines in European commercial seafood and consumers risk assessment

Highlights: • First study of cyclic imines in commercial shellfish samples from Europe. • First study including samples from eight European countries during two years. • First report dealing risk assessment on pinnatoxins. • Completes information regarding spirolides from the EFSA report on 2010. • Increases database on levels of CIs in shellfish to perform a risk assessment. Cyclic imines constitute a quite recently discovered group of marine biotoxins that act on neural receptors and that bioaccumulate in seafood. They are grouped together due to the imino group functioning as their common pharmacore, responsible for acute neurotoxicity in mice. Cyclic imines (CIs) have not been linked yet to human poisoning and are not regulated in the European Union (EU), although the European Food Safety Authority (EFSA) requires more data to perform conclusive risk assessment for consumers. Several commercial samples of bivalves including raw and processed samples from eight countries (Italy, Portugal, Slovenia, Spain, Ireland, Norway, The Netherlands and Denmark) were obtained over 2 years. Emerging cyclic imine concentrations in all the samples were analysed on a LC-3200QTRAP and LC-HRMS QExactive mass spectrometer. In shellfish, two CIs, pinnatoxin G (PnTX-G) and 13-desmethylspirolide C (SPX-1) were found at low concentrations (0.1–12 µg/kg PnTX-G and 26–66 µg/kg SPX-1), while gymnodimines and pteriatoxins were not detected in commercial (raw and processed) samples. In summary, SPX-1 (n: 47) and PnTX-G (n: 96) were detected in 9.4% and 4.2% of the samples, respectively, at concentrations higher than the limit of quantification (LOQ), and in 7.3% and 31.2% of the samples at concentrations lower than the LOQ (25 µg/kg for SPX-1 and 3 µg/kg for PnTX-G), respectively. For the detected cyclic imines, the average exposure and the 95th percentile were calculated. The results obtained indicate that it is unlikely that a potential health risk exists through the seafood diet for CIs in the EU. However, further information about CIs is necessary in order to perform a conclusive risk assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Aerosol sources in subway environments

Highlights: • PM{sub 2.5} concentrations varied widely among subway platforms (26–86 µg m{sup −3}). • Main PM{sub 2.5} component in metro microenvironment is iron oxide. • Subway sources contribution account for up to 91% of ambient subway PM{sub 2.5}. • From the five subway-specific sources identified, brakes contributed the most. • Elements related with health issues are apportioned mostly by subway sources (> 60%). Millions of people use rail subway public transport around the world, despite the relatively high particulate matter (PM) concentrations in these underground environments, requiring the identification and quantification of the aerosol source contributions to improve the air quality. An extensive aerosol monitoring campaign was carried out in eleven subway stations in the Barcelona metro system, belonging to seven subway lines. PM{sub 2.5} samples were collected during the metro operating hours and chemically analysed to determine major and trace elements, inorganic ions, and total carbon. The chemical compositions of subway components such as brake pads, rail tracks and pantographs were also determined. The mean PM{sub 2.5} concentrations varied widely among stations, ranging from 26 µg m{sup −3} to 86 µg m{sup −3}. Subway PM{sub 2.5} was mainly constituted by Fe{sub 2}O{sub 3} (30–66%), followed by carbonaceous matter (18–37%) for the old stations, while for new stations equipped with Platform Screen Doors (PSD) these percentages go down to 21–44% and 15–30%, respectively. Both the absolute concentrations and the relative abundance of key species differed for each subway station, although with common patterns within a given subway line. This is a result of the different emission chemical profiles in different subway lines (using diverse types of brakes and/or pantographs). The co-emission of different sources poses a problem for their separation by receptor models. Nevertheless, receptor modelling (Positive Matrix Factorization) was applied resulting in ten sources, five of them subway-specific: RailWheel, RailWheel+Brake, Brake{sub A}, Brake{sub B}, Pb. The sum of their contributions accounted for 43–91% of bulk PM{sub 2.5} for the old stations and 21–52% for the stations with PSD. The decrease of the activity during the weekends resulted in a decrease (up to 56%) in the subway-specific sources contribution to the –already lower– bulk PM{sub 2.5} concentrations compared to weekdays. The health-related elements are mainly apportioned (> 60%) by subway sources.

54 ENVIRONMENTAL SCIENCES↗