Publications by authors named "Ramon A Alvarez"

Article Synopsis
  • New environmental justice laws in the U.S. aim to tackle unfair air pollution levels that affect people in different areas, especially where health issues are worsened by bad air quality.
  • The goal is to find better ways to measure and track these pollution problems to ensure they are being solved effectively.
  • Recent federal funding offers a great chance for scientists and government officials to work together to improve air quality and reduce health risks from pollution for everyone.
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We performed more than a year of mobile, 1 Hz measurements of lung-deposited surface area (LDSA, the surface area of 20-400 nm diameter particles, deposited in alveolar regions of lungs) and optically assessed fine particulate matter (PM), black carbon (BC), and nitrogen dioxide (NO) in central London. We spatially correlated these pollutants to two urban emission sources: major roadways and restaurants. We show that optical PM is an ineffective indicator of tailpipe emissions on major roadways, where we do observe statistically higher LDSA, BC, and NO.

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Urban concentrations of black carbon (BC) and other primary pollutants vary on small spatial scales (<100m). Mobile air pollution measurements can provide information on fine-scale spatial variation, thereby informing exposure assessment and mitigation efforts. However, the temporal sparsity of these measurements presents a challenge for estimating representative long-term concentrations.

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Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production.

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Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO) concentrations within 24 census tracts across Houston, Texas.

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Article Synopsis
  • Methane emissions from the U.S. oil and natural gas supply chain were assessed using ground measurements and aircraft validations in regions covering about 30% of gas production, leading to an estimated emission of 13 ± 2 teragrams per year for 2015.
  • This estimate represents 2.3% of the total U.S. gas production and is about 60% higher than the EPA's existing inventory, highlighting gaps in current emission tracking methods.
  • Effective measures for emission reductions can be achieved by quickly identifying causes of high emissions and implementing more reliable systems.
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  • Metallic nanoalloys exhibit promising applications in fields like biomedicine, electrocatalysis, and sensors due to their unique properties.
  • A new low-toxicity synthesis method was developed for creating nanowire networks and Ag-Au hollow nanospheres at room temperature without complex equipment.
  • The resulting nanostructures showed small diameters (10-13 nm for NWNs and 70-130 nm for hollow nanospheres) and stable UV-vis spectrum absorption bands, demonstrating efficiency and longevity in their production.
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Effectively mitigating methane emissions from the natural gas supply chain requires addressing the disproportionate influence of high-emitting sources. Here we use a Monte Carlo simulation to aggregate methane emissions from all components on natural gas production sites in the Barnett Shale production region (Texas). Our total emission estimates are two-thirds of those derived from independent site-based measurements.

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Oil and gas (O&G) well pads with high hydrocarbon emission rates may disproportionally contribute to total methane and volatile organic compound (VOC) emissions from the production sector. In turn, these emissions may be missing from most bottom-up emission inventories. We performed helicopter-based infrared camera surveys of more than 8000 O&G well pads in seven U.

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Article Synopsis
  • Estimates of methane emissions from atmospheric data are higher than those from traditional inventories, causing debate over the climate impact of switching to natural gas from coal or petroleum.
  • A study in Texas's Barnett Shale shows that both top-down and bottom-up methane emissions estimates align within a 10% difference, which eases some of the conflicting claims.
  • High-emission oil and gas facilities are concentrated, with only 2% of them responsible for half of the methane emissions, and the estimated methane losses increase the short-term climate impact of natural gas by about 50%.
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Emissions from natural gas production sites are characterized by skewed distributions, where a small percentage of sites-commonly labeled super-emitters-account for a majority of emissions. A better characterization of super-emitters is needed to operationalize ways to identify them and reduce emissions. We designed a conceptual framework that functionally defines superemitting sites as those with the highest proportional loss rates (methane emitted relative to methane produced).

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Methane emissions from the oil and gas industry (O&G) and other sources in the Barnett Shale region were estimated by constructing a spatially resolved emission inventory. Eighteen source categories were estimated using multiple data sets, including new empirical measurements at regional O&G sites and a national study of gathering and processing facilities. Spatially referenced activity data were compiled from federal and state databases and combined with O&G facility emission factors calculated using Monte Carlo simulations that account for high emission sites representing the very upper portion, or fat-tail, in the observed emissions distributions.

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While natural gas produces lower carbon dioxide emissions than diesel during combustion, if enough methane is emitted across the fuel cycle, then switching a heavy-duty truck fleet from diesel to natural gas can produce net climate damages (more radiative forcing) for decades. Using the Technology Warming Potential methodology, we assess the climate implications of a diesel to natural gas switch in heavy-duty trucks. We consider spark ignition (SI) and high-pressure direct injection (HPDI) natural gas engines and compressed and liquefied natural gas.

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Natural gas is seen by many as the future of American energy: a fuel that can provide energy independence and reduce greenhouse gas emissions in the process. However, there has also been confusion about the climate implications of increased use of natural gas for electric power and transportation. We propose and illustrate the use of technology warming potentials as a robust and transparent way to compare the cumulative radiative forcing created by alternative technologies fueled by natural gas and oil or coal by using the best available estimates of greenhouse gas emissions from each fuel cycle (i.

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Development of the eyes during the larval and metamorphic stages of the turbot Psetta maxima (Teleosti) was studied using microscopy. Events during differentiation of both eyes occur simultaneously, and no differences between he migrating and no-migrating eye were observed during metamorphosis. At hatching, the eyes are rudimentary, consisting of a neuroepithelial optic cup and a small lens.

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