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Browse publications gathered by the California Energy Commission that focus on climate change issues relevant to the State of California. Find both PIER research papers as well as relevant articles published in peer reviewed journals.

Publications Published in 2010

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  1. Characterization of the Single Particle Mixing State of Individual Ship Plume Events Measured at the Port of Los Angeles. Ault AP, Gaston CI, Wang Y, Dominguez G, Thiemens MH, Prather KA.
    Environmental Science & Technology: 2010
    http://pubs.acs.org/doi/abs/10.1021/es902985h
    Notes
    Ship emissions contribute significantly to gaseous and particulate pollution worldwide. To better understand the impact of ship emissions on air quality, measurements of the sizeresolved chemistry of individual particles in ship emissions were made at the Port of Los Angeles using real-time, singleparticle mass spectrometry. Ship plumes were identified through a combination of ship position information and measurements of gases and aerosol particles at a site 500 m from the center of the main shipping channel at the Port of Los Angeles. Single particles containing mixtures of organic carbon, vanadium, and sulfate (OC-V-sulfate) resulted from residual fuel combustion (i.e., bunker fuel),whereashigh quantities of fresh soot particles (when OC-V-sulfate particles were not present) represented distinct markers for plumes from distillate fuel combustion (i.e., diesel fuel) from ships as well as trucks in the port area. OC-V-sulfate particles from residual fuel combustion contained significantly higher levels of s lfate and sulfuric acid than plume particles containing no vanadium. These associations may be due to vanadium (or other metals such as iron) in the fuel catalyzing the oxidation of SO2 to produce sulfate and sulfuric acid on these particles. Enhanced sulfate production on OC-V-sulfate ship emission particles would help explain some of the higher than expected sulfate levels measured in California compared to models based on emissions inventories and typical sulfate production pathways. Understanding the overall impact of ships emissions is critical for controlling regional air quality in the many populated coastal regions of the world.


  2. Climate Change, Atmospheric Rivers, and Floods in California-- A Multimodel Analysis of Storm Frequency and Magnitude Changes. Dettinger, Michael.
    Journal of the American Water Resource Association: 2010
    Notes
    Recent studies have documented the important role that ''atmospheric rivers'' (ARs) of concentrated near-surface water vapor above the Pacific Ocean play in the storms and floods in California, Oregon, and Washington. By delivering large masses of warm, moist air (sometimes directly from the Tropics), ARs establish conditions for the kinds of high snowlines and copious orographic rainfall that have caused the largest historical storms. In many California rivers, essentially all major historical floods have been associated with AR storms. As an example of the kinds of storm changes that may influence future flood frequencies, the occurrence of such storms in historical observations and in a 7-model ensemble of historical-climate and projected future climate simulations is evaluated. Under an A2 greenhouse-gas emissions scenario (with emissions accelerating throughout the 21st Century), average AR statistics do not change much in most climate models; however, extremes change notably. Years with many AR episodes increase, ARs with higher-than-historical water-vapor transport rates increase, and AR storm-temperatures increase. Furthermore, the peak season within which most ARs occur is commonly projected to lengthen, extending the flood-hazard season. All of these tendencies could increase opportunities for both more frequent and more severe floods in California under projected climate changes.


  3. Climate Signal Propagation in Southern California Aquifers. Janet Barco, Terri S. Hogue, Manuela Girotto Donald R. Kendall Mario Putti.
    Water Resources Research: 2010
    Notes
    The western United States is marked by limited water resources and a fast-growing population. Increasing climate variability as well as a growing demand on water resources highlights the need for improved understanding of linkages between regional climate, surface water dynamics and groundwater recharge. The current study focuses on the linkages between climate variability and groundwater levels in Calleguas Creek watershed located in southern California. Calleguas Creek groundwater system serves as a critical source of water supply for agricultural and industrial use. Precipitation time series and groundwater levels were analyzed throughout Calleguas Creek groundwater basins for the period 1975-2004. Water level variability was analyzed for over 311 individual wells with a subset of 19 wells selected for further analysis. A correlation matrix was computed to establish well locations (or groups) with similar hydrologic behavior. Prewhitening methods were used to evaluate the effect of time-series autocorrela ion on the test statistics for trend detection using the Mann-Kendall test. Both climate and selected groundwater level (well) data were subjected to frequency analysis using Fast Fourier Transform (FFT). The time series of precipitation, the El Nino Southern Oscillation (ENSO) index, and well levels were analyzed. A strong persistence was observed in the groundwater level time series, ranging from 66- 99 %. Results suggest the existence of significant periodicities between 2.0 and 7.0 years in both the precipitation and the well level data that are partially coincident with ENSO modes. A decadal oscillation was also observed in the well level data, which partially corresponds with the Pacific Decadal Oscillation (PDO). Assessment of the complex interactions between climate variability and groundwater levels will facilitate improved water resources planning and management in water-stressed regions where marginal changes in hydrologic budgets have large implications.


  4. Compliance Responsibility and Allowance Allocation in a Carbon Dioxide (CO2) Emissions Cap-and-Trade Program for the Electricity Sector in California. Karen Palmer, Dallas Burtraw, Anthony Paul.
    : 2010
    http://www.energy.ca.gov/publications/displayOneReport.php?pubNum=CEC-500-2010-001#
    Notes
    _x000B_The regulation of greenhouse gas emissions from the electricity sector within a cap-and-trade system poses significant policy questions on where to locate the point of compliance and how to allocate tradable emission allowances. The point of compliance addresses where, in the supply chain linking fuel suppliers, generators, the transmission system, and retail local distribution companies, should the obligation for measurement and compliance be placed. This problem is examined in the specific context of California�s legislative requirements and energy markets, and different policy options explored. The conclusion offered is that one particular approach to regulating the electricity sector�the first-seller (first deliverer) approach�would be best for California. How to allocate emission allowances is important because allocation conveys tremendous value and can have efficiency consequences. This research uses simulation modeling for the electricity sector to examine different approaches to allocation and how it affects prices and other aspects of the electricity sector, as well as implications for the overall cost of climate policy for the California economy. An important issue that influences both questions about point of compliance and method of allocation is the opportunity for emission reductions in California to be offset by emission increases in neighboring regions that supply electricity to the state. This study finds the amount of emission leakage (i.e. an increase in CO2 emissions outside of California as a result of the program) varies with the regulatory design of the program._x000B_


  5. Direct Measurements of the Ozone Formation Potential from Livestock and Poultry Waste Emissions. Cody J. Howard, Anuj Kumar, Frank Mitloehner, Kimberly Stackhouse, Peter G. Green, Robert G. Flocchini and Michael J. Kleeman.
    Environmental Science & Technology: 2010
    http://dx.doi.org/10.1021/es901916b
    DOI: 10.1021/es901916b
    Notes
    The global pattern of expanding urban centers and increasing agricultural intensity is leading to more frequent interactions between air pollution emissions from urban and agricultural sources. The confluence of these emissions that traditionally have been separated by hundreds of kilometers is creating new air quality challenges in numerous regions across the United States. An area of particular interest is California's San Joaquin Valley (SJV), which has an agricultural output higher than many countries, a rapidly expanding human population, and ozone concentrations that are already higher than many dense urban areas. New regulations in the SJV restrict emissions of reactive organic gases (ROGs) from animal sources in an attempt to meet Federal and State ozone standards designed to protect human health. The objective of this work is to directly measure the ozone formation potential (OFP) of agricultural animal plus waste sources in representative urban and rural atmospheres using a transportable 'smog' cha ber. Four animal types were examined: beef cattle, dairy cattle, swine, and poultry. Emissions from each animal plus waste type were captured in a 1 m3 Teflon bag, mixed with representative background NOx and ROG concentrations, and then exposed to UV radiation so that ozone formation could be quantified. The emitted ROG composition was also measured so that the theoretical incremental reactivity could be calculated for a variety of atmospheres and directly compared with the measured OFPunder the experimental conditions. The results demonstrate that OFP associated with waste ROG emissions from swine (0.39 ( 0.04 g-O3 per g-ROG), beef cattle (0.51 ( 0.10 g-O3 per g-ROG), and dairy cattle (0.42 ( 0.07 g-O3 per g-ROG) are lower than OFP associated with ROG emissions from gasoline powered light-duty vehicles (LDV) (0.69 ( 0.05 g-O3 per g-ROG). The OFP of ROG emitted from poultry waste (1.35 ( 0.73 g-O3 per g-ROG) is approximately double the LDV OFP. The measured composition of ROG emitted from animal plus waste ources is nine times less reactive than the current regulatory profiles that are based on dated measurements. The new animal waste ROG OFP measurements combined with adjusted animal wasteROGemissions inventory estimates predict that actual ozone production in the SJV from livestock and poultry (5.7 ( 1.3 tons O3 day-1) is 40 ( 10% of the ozone produced by light duty gasoline vehicles (14.3(1.4 tonsO3 day-1) under constant NOx conditions.


  6. Ecosystem Feedbacks to Climate Change in California: Development, Testing, and Analysis Using a Coupled Regional Atmosphere and Land Surface Model (WRF3-CLM3.5). Z. M. Subin, W. J. Riley, J. Jin D. S. Christianson M. S. Torn & Kueppers, L. M..
    Earth Interactions: 2010
    Notes
    A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3- CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical luid Dynamics Laboratory ClimateModel version 2.1 (GFDL CM2.1). The landcover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of 20.78 to 118C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.28- 1.28C reductions in summer daily-mean 2-m air temperature and 2.08-3.78C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate-vegetation interactions.


  7. Enzootic and epizootic dynamics of the chytrid fungal pathogen of amphibians. Cheryl J. Briggsa, Roland A. Knappb, Vance T. Vredenburgc.
    PNAS: 2010
    http://dx.doi.org/10.1073/pnas.0912886107
    DOI: 10.1073/pnas.0912886107
    Notes
    Chytridiomycosis, the disease caused by the chytrid fungus, Batrachochytrium dendrobatidis (Bd), has contributed to amphibian population declines and extinctions worldwide. The impact of this pathogen, however, varies markedly among amphibian species and populations. Following invasion into some areas of California's Sierra Nevada, Bd leads to rapid declines and local extinctions of frog populations (Rana muscosa, R. sierrae). In other areas, infected populations of the same frog species have declined but persisted at low host densities for many years. We present results of a 5-year study showing that infected adult frogs in persistent populations have low fungal loads, are surviving between years, and frequently lose and regain the infection. Here we put forward the hypothesis that fungal load dynamics can explain the different population-level outcomes of Bd observed in different areas of the Sierra Nevada and possibly throughout the world. We develop a model that incorporates the biological details of the Bd-host interaction. Importantly, model results suggest that host persistence versus extinction does not require differences in host susceptibility, pathogen virulence, or environmental conditions, and may be just epidemic and endemic population dynamics of the same host-pathogen system. The different disease outcomes seen in natural populations may result solely from density-dependent host-pathogen dynamics. The model also shows that persistence of Bd is enhanced by the long-lived tadpole stage that characterize these two frog species, and by nonhost Bd reservoirs.


  8. Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements. Bin Guan, Duane E. Waliser, Noah P. Molotch, Eric J. Fetzer & Paul J. Neiman.
    Geophysical Research Letters: 2010
    http://dx.doi.org/10.1029/2010GL044696
    DOI: 10.1029/2010GL044696
    Notes
    Narrow bands of strong atmospheric water vapor transport, referred to as “atmospheric rivers” (ARs), are responsible for the majority of wintertime extreme precipitation events with important contributions to the seasonal water balance. We investigate relationships between snow water equivalent (SWE), precipitation, and surface air temperature (SAT) across the Sierra Nevada for 45 wintertime AR events. Analysis of assimilated and in situ data for water years 2004–2010 indicates that ARs on average generate ∼4 times daily SWE accumulation of non-AR storms. In addition, AR events contributed ∼30–40% of total seasonal SWE accumulation in most years, with the contribution dominated by just 1–2 extreme events in some cases. In situ and remotely sensed observations show that SWE changes associated with ARs are closely related to SAT. These results reveal the previously unexplored significance of ARs with regard to the snowpack and associated sensitivities of AR precipitation to SAT.


  9. Fine scale modeling of wintertime aerosol mass, number, and size distributions in central California. Yang Zhang, Ping Liu, Xiao-Huan Liu, Betty Pun, Christian Seigneur, Mark Z. Jacobson, Wen-Xing Wang.
    Wiley Online Library Journal of Geophysical Research: Atmospheres: 2010
    http://onlinelibrary.wiley.com/doi/10.1029/2009JD012950/abstract
    DOI: 10.1029/2009JD012950
    Notes
    In light of non-attainment of PM2.5 in central California, the CMAQ-MADRID 1 model is applied to simulate PM2.5 mass, number, and size distributions observed during the Californi Regional PM a 10/PM2.5 Air Quality Study (CRPAQS) winter episode of 25-31 December 2000. The simulations with 12 and 24 size sections at a horizontal grid resolution of 4-km reproduce well the 24-hr average mass concentrations of PM2.5 (with normalized mean biases (NMBs) of - 6.2% to 0.5%), but with larger biases for organic matter, nitrate, and elemental carbon (with NMBs of -67% to 40.2%) and a weaker capability of replicating temporal variation of PM2.5 and its components. The coagulation process leads to a 40-91% reduction in simulated PM2.5 number concentrations. The 24-section simulation with coagulation shows the best agreement with the observed PM number and size distributions (with an NMB of -13.9%), indicating the importance of coagulation for predicting particle number and the merits of using a fine particle size resoluti n. Accurately simulating PM2.5 number and size distributions continues to be a major challenge, due to inaccuracies in model inputs (e.g., meteorological fields, precursor emissions, and the initial size distribution of PM emissions and concentrations), uncertainties in model formulations (e.g., heterogeneous chemistry, and aerosol formation, growth, and removal processes), as well as inconsistencies and uncertainties in observations obtained with different methods.


  10. Forest carbon densities and uncertainties from Lidar, QuickBird, and field measurements in California. Patrick Gonzalez, Gregory P. Asner, John J. Battles Michael A. Lefsky Kristen M. Waring Michael Palace.
    Remote Sensing Environment: 2010
    Notes
    Greenhouse gas inventories and emissions reduction programs require robust methods to quantify carbon sequestration in forests. We compare forest carbon estimates from Light Detection and Ranging (Lidar) data and QuickBird high-resolution satellite images, calibrated and validated by field measurements of individual trees. We conducted the tests at two sites in California: (1) 59 km2 of secondary and old-growth coast redwood (Sequoia sempervirens) forest (Garcia–Mailliard area) and (2) 58 km2 of old-growth Sierra Nevada forest (North Yuba area). Regression of aboveground live tree carbon density, calculated from field measurements, against Lidar height metrics and against QuickBird-derived tree crown diameter generated equations of carbon density as a function of the remote sensing parameters. Employing Monte Carlo methods, we quantified uncertainties of forest carbon estimates from uncertainties in field measurements, remote sensing accuracy, biomass regression equations, and spatial autocorrelation. Validation of QuickBird crown diameters against field measurements of the same trees showed significant correlation (r = 0.82, P < 0.05). Comparison of stand-level Lidar height metrics with field-derived Lorey's mean height showed significant correlation (Garcia–Mailliard r = 0.94, P < 0.0001; North Yuba R = 0.89, P < 0.0001). Field measurements of five aboveground carbon pools (live trees, dead trees, shrubs, coarse woody debris, and litter) yielded aboveground carbon densities (mean ± standard error without Monte Carlo) as high as 320 ± 35 Mg ha− 1 (old-growth coast redwood) and 510 ± 120 Mg ha− 1 (red fir [Abies magnifica] forest), as great or greater than tropical rainforest. Lidar and QuickBird detected aboveground carbon in live trees, 70–97% of the total. Large sample sizes in the Monte Carlo analyses of remote sensing data generated low estimates of uncertainty. Lidar showed lower uncertainty and higher accuracy than QuickBird, due to high correlation of biomass to height and undercounting of trees by the crown detection algorithm. Lidar achieved uncertainties of < 1%, providing estimates of aboveground live tree carbon density (mean ± 95% confidence interval with Monte Carlo) of 82 ± 0.7 Mg ha− 1 in Garcia–Mailliard and 140 ± 0.9 Mg ha− 1 in North Yuba. The method that we tested, combining field measurements, Lidar, and Monte Carlo, can produce robust wall-to-wall spatial data on forest carbon.


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