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1.
Environ Sci Technol ; 52(17): 10205-10213, 2018 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-30071722

RESUMO

We estimate postmeter methane (CH4) emissions from California's residential natural gas (NG) system using measurements and analysis from a sample of homes and appliances. Quiescent whole-house emissions (i.e., pipe leaks and pilot lights) were measured using a mass balance method in 75 California homes, while CH4 to CO2 emission ratios were measured for steady operation of individual combustion appliances and, separately, for transient operation of three tankless water heaters. Measured quiescent whole-house emissions are typically <1 g CH4/day, though they exhibit long-tailed gamma distributions containing values >10 g CH4/day. Most operating appliances yield undetectable CH4 to CO2 enhancements in steady operation (<0.01% of gas consumed), though storage water heaters and stovetops exhibit long-tailed gamma distributions containing high values (∼1-3% of gas consumed), and transients are observed for the tankless heaters. Extrapolating results to the state-level using Bayesian Markov chain Monte Carlo sampling combined with California housing statistics and gas use information suggests quiescent house leakage of 23.4 (13.7-45.6, at 95% confidence) Gg CH4, with pilot lights contributing ∼30%. Emissions from steady operation of appliances and their pilots are 13.3 (6.6-37.1) Gg CH4/yr, an order of magnitude larger than current inventory estimates, with transients likely increasing appliance emissions further. Together, emissions from residential NG are 35.7 (21.7-64.0) Gg CH4/yr, equivalent to ∼15% of California's NG CH4 emissions, suggesting leak repair, improvement of combustion appliances, and adoption of nonfossil energy heating sources can help California meet its 2050 climate goals.


Assuntos
Poluentes Atmosféricos , Gás Natural , Teorema de Bayes , California , Metano
2.
Travel Med Infect Dis ; 7(4): 181-91, 2009 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-19717097

RESUMO

BACKGROUND: A stochastic discrete event simulation model was developed to assess the effectiveness of passenger screening for Pandemic Influenza (PI) at U.S. airport foreign entry. METHODS: International passengers arriving at 18 U.S. airports from Asia, Europe, South America, and Canada were assigned to one of three states: not infected, infected with PI, infected with other respiratory illness. Passengers passed through layered screening then exited the model. 80% screening effectiveness was assumed for symptomatic passengers; 6% asymptomatic passengers. RESULTS: In the first 100 days of a global pandemic, U.S. airport screening would evaluate over 17 M passengers with 800 K secondary screenings. 11,570 PI infected passengers (majority asymptomatic) would enter the U.S. undetected from all 18 airports. Foreign airport departure screening significantly decreased the false negative (infected/undetected) passengers. U.S. attack rates: no screening (26.9%-30.9%); screening (26.4%-30.6%); however airport screening results in 800 K-1.8 M less U.S. PI cases; 16 K-35 K less deaths (2% fatality rate). Antiviral medications for travel contact prophylaxis (10 contacts/PI passenger) were high - 8.8M. False positives from all 18 airports: 100-200/day. CONCLUSIONS: Foreign shore exit screening greatly reduces numbers of PI infected passengers. U.S. airport screening identifies 50% infected individuals; efficacy is limited by the asymptomatic PI infected. Screening will not significantly delay arrival of PI via international air transport, but will reduce the rate of new US cases and subsequent deaths.


Assuntos
Aeronaves , Surtos de Doenças/prevenção & controle , Influenza Humana/prevenção & controle , Modelos Estatísticos , Viagem , Simulação por Computador , Europa (Continente) , Humanos , Cooperação Internacional , Programas de Rastreamento/métodos , Vigilância da População/métodos , Processos Estocásticos , Estados Unidos
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