Mortality burdens in California due to air pollution attributable to local and nonlocal emissions.

Limited research has been conducted on the contributions of local and nonlocal emission sources to ambient fine particulate matter (PM2.5) and ozone (O3) and their associated mortality. In this study, we estimated the total mortality resulting from long-term PM2.5 and O3 exposures in California in 2012 using multiple concentration response functions (CRFs) and attributed the estimated mortality to different emission groups. The point estimates of PM2.5-associated mortality in California ranged from 12,700 to 26,700, of which 53% were attributable to in-state anthropogenic emissions. Based on new epidemiological evidence, we estimated that O3 could be associated with up to 13,700 deaths from diseases of both the respiratory and cardiovascular systems in California. In addition, 75% of the ambient O3 in California was due to distant emissions outside the western United States, leading to 92% of the O3-associated mortality. Overall, distant emissions lead to greater mortality burdens of air pollution in California than local anthropogenic emissions

Satellite Analyses of Cirrus Cloud Properties During the FIRE Phase 2 Cirrus Intensive Field Observations over Kansas

The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances

Simulation of the global contrail radiative forcing: A sensitivity analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96352/1/grl29839.pd

Modeling of Turbulent Swirling Flows

Aircraft engine combustors generally involve turbulent swirling flows in order to enhance fuel-air mixing and flame stabilization. It has long been recognized that eddy viscosity turbulence models are unable to appropriately model swirling flows. Therefore, it has been suggested that, for the modeling of these flows, a second order closure scheme should be considered because of its ability in the modeling of rotational and curvature effects. However, this scheme will require solution of many complicated second moment transport equations (six Reynolds stresses plus other scalar fluxes and variances), which is a difficult task for any CFD implementations. Also, this scheme will require a large amount of computer resources for a general combustor swirling flow. This report is devoted to the development of a cubic Reynolds stress-strain model for turbulent swirling flows, and was inspired by the work of Launder's group at UMIST. Using this type of model, one only needs to solve two turbulence equations, one for the turbulent kinetic energy k and the other for the dissipation rate epsilon. The cubic model developed in this report is based on a general Reynolds stress-strain relationship. Two flows have been chosen for model evaluation. One is a fully developed rotating pipe flow, and the other is a more complex flow with swirl and recirculation

Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

Aerosol‐cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9‐year satellite retrievals, we find that, for convection‐generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small‐to‐moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection‐generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol‐ice cloud radiative forcing

Remote sensing estimates of cirrus particle size for tropical and midlatitude cirrus: Hexagonal crystals and ice spheres

A large discrepancy exists in current estimates of a mean cirrus particle size appropriate for calculations of the effects of these ice clouds on solar and thermal infrared radiative fluxes. For spheres with large size parameter (x = (2 pi r / lambda) is greater than 30, where r is particle radius), and moderate absorption (n(sup i) x less than 1, where n(sup i) is imaginary index of refraction for ice), the optimal effective particle radius is given by: r(sub e) = integral of r(exp 3)n(r)dr / integral of r(exp 2)n(r)dr. For the remote sensing of cirrus particle size at wavelengths of 0.83, 1.65, and 2.21 mu m, a 50 mu m ice sphere would have a size parameter of about 200, and values of n(sup i) x of 0, 0.045, and 0.06, satisfying the above conditions. However, while r(sub e) is a well-defined parameter for spheres, this cross-section area-weighted particle radius can only be extended to non-spherical particles by defining some equivalent sphere, typically an equivalent volume or equivalent cross-section area sphere. Using equivalent volume spheres, values of r(sub e) obtained over Lake Michigan on October 28, 1986, during FIRE phase I varied from 200 mu m (King Air 2D Imaging probes) to 60 mu m (Landsat reflectances at 0.83, 1.65, and 2.2 mu m), to 25 mu m (HIS spectrometer thermal emission between 8 and 12 mu m). Three major uncertainties were identified in this comparison: small ice particles missed by the 2D-C aircraft probes, uncertain ice refractive index, and uncertainties in the single scatter albedos and scattering phase functions used in the radiative calculations. Since the first FIRE cirrus results, advances have been made in all three areas. The present paper reports on improvements in the radiative modeling of ice particles at 0.83, 1.65, and 2.21 mu m wavelengths appropriate for comparisons to Landsat Thematic Mapper data. The paper also includes new results for Landsat observations of ice clouds in the eastern and western tropical Pacific

Comparison of radiation and cloud parameters derived from satellite and aircraft measurements during FIRE 2 cirrus IFO

Meteorological satellite instrument pixel sizes are often much greater than the individual cloud elements in a given scene. Partially cloud-filled pixels can be misinterpreted in many analysis schemes because the techniques usually assume that all of the cloudy pixels are cloud filled. Coincident Landsat and Geostationary Operational Environmental Satellite (GOES) data and degraded-resolution Landsat data were used to study the effects of both sensor resolution and analysis techniques on satellite-derived cloud parameters. While extremely valuable for advancing the understanding of these effects, these previous studies were relatively limited in the number of cloud conditions that were observed and by the limited viewing and illumination conditions. During the First ISCCP Regional Experiment (FIRE) Phase 2 (13 Nov. - 7 Dec. 1991), the NASA ER-2 made several flights over a wide range of cloud fields and backgrounds with several high resolution sensors useful for a variety of purposes including serving as ground truth for satellite-based cloud retrievals. This paper takes a first look at utilizing the ER-2 for validating cloud parameters derived from GOES and NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data

Change in household fuels dominates the decrease in PM_(2.5) exposure and premature mortality in China in 2005–2015

To tackle the severe fine particle (PM_(2.5)) pollution in China, the government has implemented stringent control policies mainly on power plants, industry, and transportation since 2005, but estimates of the effectiveness of the policy and the temporal trends in health impacts are subject to large uncertainties. By adopting an integrated approach that combines chemical transport simulation, ambient/household exposure evaluation, and health-impact assessment, we find that the integrated population-weighted exposure to PM_(2.5) (IPWE) decreased by 47% (95% confidence interval, 37–55%) from 2005 [180 (146–219) μg/m^3] to 2015 [96 (83–111) μg/m^3]. Unexpectedly, 90% (86–93%) of such reduction is attributed to reduced household solid-fuel use, primarily resulting from rapid urbanization and improved incomes rather than specific control policies. The IPWE due to household fuels for both cooking and heating decreased, but the impact of cooking is significantly larger. The reduced household-related IPWE is estimated to avoid 0.40 (0.25–0.57) million premature deaths annually, accounting for 33% of the PM_(2.5)-induced mortality in 2015. The IPWE would be further reduced by 63% (57–68%) if the remaining household solid fuels were replaced by clean fuels, which would avoid an additional 0.51 (0.40–0.64) million premature deaths. Such a transition to clean fuels, especially for heating, requires technology innovation and policy support to overcome the barriers of high cost of distribution systems, as is recently being attempted in the Beijing–Tianjin–Hebei area. We suggest that household-fuel use be more highly prioritized in national control policies, considering its effects on PM_(2.5) exposures

A modeling study of the nonlinear response of fine particles to air pollutant emissions in the Beijing-Tianjin-Hebei region

The Beijing–Tianjin–Hebei (BTH) region has been suffering from the most severe fine-particle (PM2:5) pollution in China, which causes serious health damage and economic loss. Quantifying the source contributions to PM2:5 concentrations has been a challenging task because of the complicated nonlinear relationships between PM2:5 concentrations and emissions of multiple pollutants from multiple spatial regions and economic sectors. In this study, we use the extended response surface modeling (ERSM) technique to investigate the nonlinear response of PM2:5 concentrations to emissions of multiple pollutants from different regions and sectors over the BTH region, based on over 1000 simulations by a chemical transport model (CTM). The ERSM-predicted PM2:5 concentrations agree well with independent CTM simulations, with correlation coefficients larger than 0.99 and mean normalized errors less than 1 %. Using the ERSM technique, we find that, among all air pollutants, primary inorganic PM2:5 makes the largest contribution (24–36 %) to PM2:5 concentrations. The contribution of primary inorganic PM2:5 emissions is especially high in heavily polluted winter and is dominated by the industry as well as residential and commercial sectors, which should be prioritized in PM2:5 control strategies. The total contributions of all precursors (nitrogen oxides, NOx ; sulfur dioxides, SO2; ammonia, NH3; non-methane volatile organic compounds, NMVOCs; intermediate-volatility organic compounds, IVOCs; primary organic aerosol, POA) to PM2:5 concentrations range between 31 and 48 %. Among these precursors, PM2:5 concentrations are primarily sensitive to the emissions of NH3, NMVOCCIVOC, and POA. The sensitivities increase substantially for NH3 and NOx and decrease slightly for POA and NMVOCCIVOC with the increase in the emission reduction ratio, which illustrates the nonlinear relationships between precursor emissions and PM2:5 concentrations. The contributions of primary inorganic PM2:5 emissions to PM2:5 concentrations are dominated by local emission sources, which account for over 75% of the total primary inorganic PM2:5 contributions. For precursors, however, emissions from other regions could play similar roles to local emission sources in the summer and over the northern part of BTH. The source contribution features for various types of heavy-pollution episodes are distinctly different from each other and from the monthly mean results, illustrating that control strategies should be differentiated based on the major contributing sources during different types of episodes.publishedVersio

Modeling Study of the Air Quality Impact of Record-Breaking Southern California Wildfires in December 2017

We investigate the air quality impact of record‐breaking wildfires in Southern California during 5–18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high‐resolution (375 × 375 m²) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM_(2.5)) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM_(2.5) simulation results. Biases in PM_(2.5) simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14‐day averaged PM_(2.5) concentrations by up to 231.2 μg/m³ over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire‐induced PM_(2.5) accounts for 14–42% of the annual total PM_(2.5) exposure in areas impacted by the fire plumes