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  • Open Access English
    Authors: 
    Wang, Di;
    Publisher: eScholarship, University of California
    Country: United States

    China has experienced drastic climate change and severe environmental pollution since the 1980s. This dissertation provides economic analyses of these two types of environmental changes in China by focusing on the temporal evolution of agricultural sensitivity to extreme heat and the political economy explanations for severe air pollution in China. Chapter 1 examines the time-varying impacts of extreme temperatures on Chinese agriculture over 1981 to 2010. By estimating a period-specific panel regression model using nationwide county-level agriculture production data combined with fine-scale meteorological data, I primarily find the impact of a daily exposure to extreme temperatures on corn and soybean yields in the post-1996 period is 40% to 50% less than that in the pre-1996 period and the decline in the extreme temperature impacts on crop yields mainly occurs in counties with expanding irrigation coverage. Chapter 2 explores reasons for severe air pollution from the perspective of political economy by examining the environmental consequences of the county-to-city upgrading policy which delegates the autonomy of building cities to upgraded counties. In a centralized system like China, economic decentralization without changing the promotion metrics centered around economic performance for local government officials would likely lead to worse environmental quality because local officials compete for promotion on economic performance. Using a comprehensive county-level dataset on economic performance indicators and air pollutant concentrations, I primarily find significantly positive policy effects on economic growth and air pollutant concentrations, suggesting that the upgraded counties promoted economic performance at the cost of local air quality. I also calculate the total loss due to the increasing air pollution as valued in terms of statistical life to indicate the magnitude of the social cost of the upgrading policy. Following the finding of decline in agricultural sensitivity to extreme heat in Chapter 1, Chapter 3 quantifies the contribution of the temporal evolution of extreme temperature impacts to the growth of agricultural revenue during 1981-2010 using an Oaxaca-Blinder decomposition which attributes the growth of agricultural revenue to the change in the levels of predictors and to the change in the coefficients for the predictors. I find extreme temperature impacts on agricultural revenues per hectare in the post-1996 period is more than 60% lower than that in the pre-1996 period, contributing 6.1 percentage points of revenue growth over the two periods, which is 5.4% of the overall growth of agricultural revenue. The significant increase in marginal benefit of irrigation in terms of moderating extreme temperature impacts may have contributed about 40% of the decline in the extreme temperature impacts on agricultural revenue per hectare.

  • Open Access English
    Authors: 
    Biggs, Brenna;
    Publisher: eScholarship, University of California
    Country: United States

    Many California regulations try to decelerate climate change by mitigating emissions from various industries. Greenhouse gases (GHGs) such as methane, carbon dioxide, and nitrous oxide must be fully understood to meet these strict reduction goals. Landfills release GHGs during decomposition and active dumping, while dairy farms release GHGs enterically (i.e., from cows) and from manure management. This study aims to better understand these GHGs at active and closed Orange County landfills as well as at a Visalia dairy farm in California. All samples were collected using whole air sampling techniques and analyzed using gas chromatography to identify and quantify many trace gases. Select oxygenates (i.e., methanol, ethanol, and acetaldehyde), dimethyl sulfide, and carbonyl sulfide were also a focus at these locations. Unexpected and novel sources of these gases were revealed, which have possible implications for pollution and the global sulfur budget.Samples were collected at the landfills seasonally during four campaigns: Spring 2018, Summer 2018, Fall 2018, and Winter 2019 and at the dairy farm during five campaigns: September 2018, March 2019, June 2019, September 2019, and January 2020. Samples from both industries were compared to airborne and remote air samples to determine their enhancements relative to background concentrations. This research establishes previously unexplored or misrepresented sources of various gases, which is important for the success of the state’s reduction efforts, the environment, and the health of surrounding communities.California’s San Joaquin Valley, an extremely productive agricultural area, also contains many disadvantaged communities. Residents typically experience low socioeconomic status and a disproportionate amount of air pollution, which can lead to health problems. In addition to GHGs, this study also explores how direct emissions from dairy farms may affect these communities living downwind throughout the San Joaquin Valley. Orange County is more affluent but is often a nonattainment area for several pollutants including ozone and particulate matter, which affect the people living there. This study explores the contribution of trace gases from dairy farms and landfills in California to the formation of pollution and odor in these surrounding communities. Solutions for decreasing trace gas emissions from these sources are also proposed.

  • Open Access English
    Authors: 
    Li, Yin;
    Publisher: eScholarship, University of California
    Country: United States

    California Assembly Bill 32 (AB32) sets the goal to reduce greenhouse gas (GHG) emissions to a level 80% below 1990 levels by 2050. This deep decarbonization target requires major technology advancement and energy structure transition to a renewable and sustainable future. The environmental aspects of such a transition should be evaluated carefully before major investments in infrastructure are made. Biogas is a promising renewable energy resource in California that shares many similarities with natural gas but with the advantage of being carbon neutral since it generates energy from organic waste. However, biogas contains trace levels of numerous chemical compounds that depend on the feedstock and production process. The air quality implications of using biogas in different situations should be examined carefully before widespread adoption across California. The second chapter of this thesis characterizes the chemical and biological composition of raw biogas produced at five facilities using different feedstocks. The toxicity of combusted biogas is tested under fresh and photo-chemically aged conditions. Results find no strong evidence of potential occupational health risk from the five California biogas sites. Results also show no obvious differences between the toxicity of different biogas combustion exhaust after atmospheric dilution and aging. The third chapter of this thesis examines the emissions from the combustion of upgraded biogas that has CO2 removed and CH4 concentrated to be qualified as renewable natural gas (RNG). A light-duty cargo van was tested with CNG and two RNG blends on a chassis dynamometer to compare the toxicity of the resulting exhaust. CNG vehicle engine exhaust showed a higher or similar level of various toxicity responses, and photochemical reactions did not seem to alter the observed trend. These preliminary results suggest that utilizing biogas for direct heat and electricity generation or as vehicle fuel after upgrading could be useful strategies to reduce carbon intensity without negatively impacting air quality or public health. The fourth chapter of this thesis extends the scope by modeling air pollutant emissions from all California socio-economic sectors under different energy scenarios in the year 2050. To study the air quality implications of some key resources and technologies in the decarbonization transition, a total of six different scenarios were analyzed for various particulate and gaseous pollutant emissions. These scenarios include: 1) a business-as-usual future reference scenario "BAU", 2) a partial GHG reduction scenario that constrains only through 2030 with 40% reduction "CAP30", 3) a climate-friendly 80% GHG reduction scenario featuring deep penetration of advanced technologies and renewable energies "GHGAi", a same 80% GHG reduction scenario with the deployment of biomass carbon capture and sequestration technology "CCS", and two variation scenarios on GHGAi that examine the effect of using more natural gas in built environment "NGB" and power generation "NGT". Results show that major air quality benefits are expected from the GHGAi scenario, which includes aggressive decarbonization of electricity supply, electrification of most end-use appliances, improvement of appliances efficiency, and deployment of low-carbon transportation fuels and technologies. Bio-CCS technology holds promise as a shortcut to GHG mitigation and the utilization of natural gas bridges the transition from traditional to renewable energy systems, but neither of these technologies appear to be optimal from a future air quality management perspective. Adoption of biogas as an energy source plays a small but constructive role in the overall transition of California’s energy system towards a low carbon future.

  • Open Access English
    Authors: 
    Ebrahimi, Siavash;
    Publisher: eScholarship, University of California
    Country: United States

    Widespread electrification, i.e., switching direct fossil fuel end-uses to electricity, coupled with renewable power use is essential to achieve aggressive greenhouse gas and criteria pollutant emission reduction targets. Few have investigated the requisite electric grid infrastructure transformation and technology path coupled with spatial and temporal resolution of criteria pollutant emissions for assessing air quality impacts. In this study, we analyze grid and emission impacts of electrifying end-use sectors while decarbonizing power generation, using detailed modeling of infrastructure stocks and economic dispatch of the electric utility grid network. Results show that decarbonizing power supply by 50% without electrifying end-use sectors can reduce total California greenhouse gas emissions by only 2%, percent while partial electrification of end-use sectors alongside decarbonizing electricity generation by 50% yields up to 20.3 percent greenhouse gas emission reductions compared to 1990 levels. Spatially and temporally resolved criteria pollutant emissions portend certain scenarios that improve air quality more than others, requiring consideration of spatial and temporal emission perturbations dictated by specific electrification end-uses and power generation technology dynamics for meeting the increased electric demand. Combustion of fossil fuels for power generation, transportation, and other end-uses have resulted in significant air quality issues in urban areas. Solving this problem as well as climate change requires a holistic approach combining improved energy efficiency, cleaner power generation and electrification of fossil fuel end uses. However, the impact of this energy transition on local air quality has not been studied in detail. In this dissertation, we analyze the emissions and air quality impacts of electrifying end-use sectors while decarbonizing power generation, using detailed modeling of infrastructure stocks and economic dispatch of the electric grid. A set of scenarios are developed to study the impacts of electrification where each end-use sector is electrified based upon the electrification potential and feasibility of implementation using the available electric technologies. In order to accommodate higher statewide electricity demand due to electrification, the electricity generation sector is decarbonized through installing higher levels of renewable power. As electrifying energy end-uses affect the magnitude and temporal distribution of electric demand, we evaluate the amount of renewable energies that must be curtailed and quantify its implications for the load- balancing of electric grid system. High curtailment of renewable power under certain scenarios suggests the necessity for substantial energy storage to balance the grid dynamics and enable integration of higher levels of renewable power. Storing the excess renewable energy in form of hydrogen is a promising solution, which not only provides temporal electric grid balancing in matters of weeks to months, but also allows decarbonizing the transport sector. In the final chapter, we present a detailed control-oriented model for a PEM electrolyzer to characterize the dynamic response of the electrolysis platform in the time scale of minutes or seconds, which will enable us to investigate new control strategies for different grid services. The model is capable of characterizing PEM electrolyzer and essential for determining control strategy that will ensure efficient and reliable operation of the electrolyzer. Besides, the PEM electrolyzer dynamic model can be employed in the optimization of sustainable energy systems.

  • Open Access English
    Authors: 
    Soukup, James Vincent;
    Publisher: eScholarship, University of California
    Country: United States

    The San Pedro Bay Port Complex is a critical piece of the world economy as a hub of good movement and its activities generate significant pollutant emissions in an air basin that frequently struggles with degraded air quality. This research explores fuel cell deployment in place of diesel combustion engines for port activities and the air quality, GHG emissions, and human health impacts as a mitigation strategy for the degraded air quality induced by the ports. Fuel cell deployments are modeled as emission reductions in the year 2035 for port activities and ambient concentrations of air pollutants are obtained by simulating atmospheric chemistry (CMAQ). Ambient pollutant concentrations are compared against national standards and human health response functions from literature to assess impacts on morbidity and mortality as well as socioeconomics. Finally, Greenhouse Gas equivalency is determined for the emissions reductions modeled for the atmospheric simulation including upstream impacts associated with displaced diesel production and new hydrogen production. Results show potential for widespread reduction in ozone and fine particulate concentrations with titration-related increases in ozone at the immediate vicinity of the port. The maximum change in ozone was calculated to be a reduction of 5.09 ppb with a corresponding reduction in PM2.5 of 2.56 µg/m3 for the same case. Human health and socioeconomic modeling predict large net health and economic benefits. The valuation of health benefits is estimated to range $3,209,700 to $7,108,100 per day using modeling strategies demonstrated by the U.S. Environmental Protection Agency and California Air Resources Board.

  • Open Access English
    Authors: 
    Hausfather, Ezekiel Jon;
    Publisher: eScholarship, University of California
    Country: United States

    The observational temperature record is a critical part of our understanding of changes in Earth’s climate. However, large uncertainties remain in our historical measurements of surface, ocean, and atmospheric temperatures. Many of these are introduced by changes in measurement techniques over time, such as changing instrumentation, time of observation, or changes to the surrounding environment not representative of the broader region. Reducing these uncertainties is important to improve our understanding of long-term climate change, and has implications for assessing the magnitude of inter-decadal climate variability, evaluating the performance of climate models, determining the remaining carbon budget to achieve mitigation targets, among other issues. This dissertation is structured around four lead-authored papers that advance our understanding of the observational temperature record. The first paper, titled Quantifying the Effect of Urbanization on U.S. Historical Climatology Network Temperature Records, quantifies the extent to which changes in urban form surrounding measurement stations have biased long-term temperature records. By comparing temperature trends at urban and rural stations using four different proxy measures of urbanity, we find systematic differences between the raw (unadjusted) urban and rural temperature trends throughout the USHCN period of record. Based on these classifications, urbanization accounts for 14% to 21% of the rise in unadjusted minimum temperatures since 1895 and 6% to 9% since 1960. The homogenization process employed by NOAA effectively removes this urban signal such that it becomes insignificant during the last 50-80 years. In contrast, prior to 1930, only about half of the urban signal is removed. This suggests that biases in the land temperature record from urbanization are potentially significant, but can be effectively detected and removed when the network of observation stations is sufficiently dense to allow for neighbor-based pairwise homogenization.The second paper is titled Evaluating the Impact of U.S. Historical Climatology Network Homogenization Using the U.S. Climate Reference Network. In this paper the homogenization of surface temperature records in the U.S. is assessed by comparing the old weather station network (USHCN) to a new state-of-the-art U.S. Climate Reference Network (USCRN). The new U.S. Climate Reference Network provides a homogenous set of surface temperature observations that can serve as an effective empirical test of adjustments to raw USHCN stations. By comparing nearby pairs of USHCN and USCRN stations, we find that adjustments make both trends and monthly anomalies from USHCN stations much more similar to those of neighboring USCRN stations for the period from 2004-2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records. The third paper, titled Assessing Recent Warming Using Instrumentally Homogeneous sea Surface Temperature Records, seeks to solve a substantial disagreement between warming rates in different Sea surface temperature (SST) records over the past two decades. SST records are subject to potential biases due to changing instrumentation and measurement practices. Significant differences exist between commonly-used composite sea surface temperature reconstructions from NOAA’s Extended Reconstruction Sea Surface Temperature (ERSST), the Hadley Centre SST data set (HadSST3), and the Japanese Meteorological Agency’s Centennial Observation-Based Estimates of SSTs (COBE-SST) in recent years. The update from ERSST version 3b to version 4 resulted in an increase in the SST trend estimate during the last 18 years from 0.07°C/decade to 0.12°C/decade, indicating a higher rate of warming in recent years and eliminating some of the apparent “pause” in global surface temperatures over that period. We show that ERSST version 4 trends generally agree with largely-independent, near-global and instrumentally-homogeneous SST measurements from floating buoys, Argo floats, and radiometer-based satellite measurements that have been developed and deployed during the past two decades. We find a large cooling bias in ERSSTv3b and smaller but significant cooling biases in HadSST3 and COBE-SST from 2003 to present with respect to most series examined. These results suggest that reported rates of SST warming in recent years have been underestimated in these three datasets due to biases in ship-based measurements.The fourth paper, titled Evaluating the Performance of Past Climate Model Projections, looks at how well historical climate models published since 1970 have performed compared to observed temperature changes in the years after they were published. Climate models provide an important way to understand future changes in the Earth’s climate. Model projections rely on two things to accurately match observations: accurate modeling of climate physics, and accurate assumptions around future emissions of CO2 and other factors affecting the climate. The best physics-based model will still be inaccurate if it projects future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2 (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2 and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts, and increases our confidence that models are accurately projecting global warming.Work done in this dissertation has had a notable impact on our understanding and estimates of temperatures. This includes ensuring that urbanization is not biasing our record of land temperatures, testing the performance of land temperature homogenization, resolving differences between ocean temperature records in recent decades, developing a novel sea surface temperature record to help better understand WW2-era uncertainties, and evaluating recent changes in ocean heat content. In an encouraging sign of the impact of our work, the new HadSST4 temperature product from the UK Met Office prominently features comparisons with the instrumentally homogenous sea surface temperature records we developed.Similarly, the work that I and coauthors have undertaken has changed the approach used in evaluating the performance of GMST climate model projections, demonstrating the need to use common coverage and blended SAT/SST fields to ensure like-to-like comparisons with observations. Evaluating the future projections of old climate models improves our confidence that the current generation of models is accurately capturing the physical processes driving GMST change. This work on evaluating old climate models will be featured prominently in Chapter 1 of the IPCC 6th Assessment Report, where I serve as a contributing author.

  • Open Access English
    Authors: 
    Baxter, Ian;
    Publisher: eScholarship, University of California
    Country: United States

    Over the past 40 years the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflects a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic (hereafter referred to as the “Pacific-Arctic teleconnection (PARC)”), which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800-yr) CESM preindustrial simulation. These results further support the role of remote SST forcing originating from the tropical Pacific in exciting significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a Cold Pacific - Warm Arctic connection.

  • Open Access English
    Authors: 
    Forrest, Kate;
    Publisher: eScholarship, University of California
    Country: United States

    For California and other parts of the world to move towards a net-zero-emission grid, potentially a 100% renewable grid, complementary technologies to support renewable solar and wind integration need to be clearly established. Specifically, the integration of variable and intermittent solar and wind renewable generation requires resources that can respond dynamically to changes in the net load in order to ensure stable grid performance. Zero-emission vehicles (ZEVs), encompassing battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs), are uniquely positioned to (1) support variable renewable generation and provide benefits to the grid while, at the same time (2) reducing emissions from the transportation sector. Due to their disproportionately large contribution to air pollution and greenhouse gas (GHG) emissions, targeting heavy-duty vehicles (HDVs) is essential if reduction goals are to be met. This work assesses the feasibility of heavy duty ZEVs (HD-ZEVs), selecting California as the example. From a technical standpoint, more than half of Class 3-7 vehicle miles travelled (VMT) can be met with heavy-duty BEV product in development today without trip modification. Class 8 trucks have a much lower BEV feasibility due to their longer trip distances and heavy-duty FCEV product becomes more likely. The challenge becomes providing carbon-free fuel, namely renewable electricity for HD-BEVs, and renewable hydrogen for HD-FCEVs. This study assesses the fuel supply chain impact of HD-ZEV deployment on GHG emissions and air quality for the year 2050. HD-BEVs relying on uncoordinated charging can increase peak load demand and hinder the target of achieving zero GHG emissions from the electric grid. Intelligent charging of HD- BEVs and renewable hydrogen production for HD-FCEVs are both effective methods for utilizing otherwise curtailed renewable generation for the support of a zero or near-zero emissions electric grid. This study also finds that moving towards an 80% reduction in GHG emissions from HDVs through ZEV adoption has the co-benefit of significantly reducing ozone and PM2.5 concentrations in key regions of California. In comparison, reducing grid emissions from an 80% reduction to a 100% clean electric grid has a significantly smaller, but not trivial, impact in criteria air pollutant concentrations.

  • Open Access English
    Authors: 
    Caubel, Julien J;
    Publisher: eScholarship, University of California
    Country: United States

    Air pollution is one of the world’s greatest environmental health risks, responsible for over 7 million premature deaths annually. Around half of these premature mortalities are linked to biomass cooking fires that release harmful air pollutants into people’s homes, such as particulate matter (PM). Although nearly 3 billion people worldwide depend on biomass cooking fuels, relatively little scientific research exists on mitigating the smoke they generate. One promising approach for reducing emissions is the injection of secondary air into the biomass cookstove’s combustion chamber. However, cold secondary air can also quench the combustion process when improperly injected, and so many secondary air injection cookstove designs do not actually reduce harmful smoke emissions relative to a traditional three stone fire (TSF). Since wood is a common cooking fuel throughout the world, this dissertation presents an experimental wood-burning cookstove platform, dubbed the ‘Modular (MOD) stove’, to identify and optimize secondary air injection parameters that reduce the emission of harmful pollutants. The MOD stove enables systematic, repeatable experiments in which various secondary air injection design features, such as flow rate and location, can be quickly and easily adjusted. Over 130 experimental trials were conducted, demonstrating that wood combustion is highly sensitive to small changes in the secondary air injection parameters. Using a systematic experimental approach, an optimal design configuration was identified that reduces mass emissions of PM2.5, carbon monoxide (CO), and black carbon (BC) by ~90% relative to a traditional TSF, while also improving thermal efficiency. Using an updated version of the MOD stove, an additional 111 performance tests were conducted to quantify the practical design requirements (e.g., secondary air pressure and temperature) to achieve ≥ 90% mass emission reductions relative to a TSF. Using this experimental data, I demonstrate that low-cost (<$10) fans and blowers are currently available to drive the secondary flow, and this hardware can be independently powered using an inexpensive thermoelectric generator mounted nearby. Furthermore, size-resolved PM measurements demonstrate that secondary air injection effectively inhibits particle growth, but the total number of particles generated remains relatively unaffected. I investigate the potential impacts for human health and explore methods to mitigate the PM formation mechanisms that persist. As a whole, the MOD stove platform demonstrates that secondary air injection is a practical, effective, and potentially economical method for meaningfully reducing smoke emissions from biomass cookstoves. However, designs should be experimentally validated and optimized, and further research is needed to eliminate the persistent formation of ultrafine particles that are particularly harmful to human health. Ambient air pollution is also widespread, and linked to significant adverse health outcomes. Over 90% of the world’s population lives in areas where ambient air pollution concentrations exceed World Health Organization recommendations, resulting in ~4 million premature deaths annually. The health impacts of ambient air pollution are particularly acute in urban settings. In 2010, premature deaths due to ambient air pollution were about 50% more common in urban than in rural environments, and this could increase to nearly 90% by 2050. Although ground-based air quality measurements are needed to address this growing health crisis, traditional regulatory monitoring networks do not provide sufficient spatial coverage and resolution to adequately assess air pollution exposures in urban environments. Distributed networks of low-cost air quality sensors are emerging to fill this gap. Black carbon (BC) is an important component of PM pollution, strongly linked to adverse human health outcomes and climate change, but low-cost sensors for monitoring this critical pollutant are lacking. This dissertation presents the Aerosol Black Carbon Detector (ABCD), specifically designed for distributed air quality monitoring networks. As such, the ABCD integrates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, outdoor deployments. Most importantly, the ABCD incorporates a number of novel design features to provide uniquely accurate BC concentration measurements in tough operating environments that debilitate existing commercial instruments. Over 100 ABCDs were operated outdoors, and their measurement performance was comparable to that of a commercial BC instrument collocated inside a regulatory monitoring station. The validated fleet of ABCDs was deployed to 100 sampling sites in West Oakland, California – a neighborhood disproportionately affected by air pollution associated with the nearby Port of Oakland and surrounding highways. Over 100 days, the wireless sensor network successfully collected 84.0% of the 240,000 hourly BC concentration measurements desired (100 sampling sites × 2,400 hours). The widespread failure of miniature vacuum pumps was responsible for most missing measurements. The resulting BC concentration maps demonstrate that concentrations vary sharply over short distances (~100 m) and timespans (~1 hour), and generally depend on surrounding land use, traffic patterns, and location relative to prevailing winds. BC concentrations at each sampling site are highly repeatable over the diurnal and weekly cycles, and periodic trends are analyzed throughout the community. Using these trends as a reference, unusually polluted locations are detected, and likely emissions sources nearby are identified. In this way, the 100x100 Network demonstrates the value of low-cost sensor networks to accurately characterize urban air pollution distributions, and provide regulatory agencies, governments, and community stakeholders with actionable insights to mitigate the sources. Air pollution is a pervasive and persistent health threat that can only be tackled if we work to both mitigate and monitor emission sources. As such, the MOD stove studies presented here are targeted towards abating the world’s deadliest polluters. However, even the best of emissions reduction efforts are left blind without accurate measurements of the resulting air quality. The ABCD meets this need, providing accurate BC monitoring capabilities in a uniquely practical and economical package. Together, these complementary technologies will help underpin more comprehensive, data-driven efforts to quantifiably reduce harmful air pollution exposure throughout the world, and ultimately prevent millions of premature deaths.

  • Open Access English
    Authors: 
    Howard, Daniel Bost;
    Publisher: eScholarship, University of California
    Country: United States

    This dissertation proposes a methodology applicable worldwide to assess key health, climate and electricity system impacts of high penetrations of variable renewable energy (VRE), such as wind and solar energy, in the production of electricity. Three primary questions are addressed: (1) what are the health benefits and control costs of tightening emission standards for particulate matter (PM); (2) what are the health, climate and electricity grid impacts of high penetrations of VRE; and (3) is a 100% Renewable Portfolio Standard (RPS) electricity grid technically feasible in Northeast (NE) Brazil, and what are the associated health and climate benefits? The methodology I developed to answer these questions combines highly resolved spatial and temporal electricity grid simulation (via Plexos), atmospheric dispersion of power plant emissions (via CALPUFF), and human health impacts estimation (via BenMAP). The methodology is validated extensively over detailed case studies in NE Brazil, a region that has exceptionally high VRE and hydroelectric potential. Results for Question (1) indicate that when tightening emission standards, the health benefits outweigh the control costs by at least 50 times, even in a relatively clean region. Results for Question (2) show that health and climate benefits exceed US$267 million/yr and US$1.2 billion/yr respectively if NE Brazil transitions to a 45% VRE instead of a 30% VRE penetration in 2030. For Question (3), I find that a 100% RPS is not feasible using only wind, solar PV and hydroelectric resources in NE Brazil unless ~13% of demand can be flexibly imported and ~23% of generation can be flexibly exported; otherwise additional types of generation, storage and load balancing technology would need to be deployed. For this case, the health and climate benefits are at least US$433 million/yr and US$2.4 billion/yr respectively if NE Brazil transitions to a 100% RPS instead of a 30% VRE penetration in 2030.

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18 Research products, page 1 of 2
  • Open Access English
    Authors: 
    Wang, Di;
    Publisher: eScholarship, University of California
    Country: United States

    China has experienced drastic climate change and severe environmental pollution since the 1980s. This dissertation provides economic analyses of these two types of environmental changes in China by focusing on the temporal evolution of agricultural sensitivity to extreme heat and the political economy explanations for severe air pollution in China. Chapter 1 examines the time-varying impacts of extreme temperatures on Chinese agriculture over 1981 to 2010. By estimating a period-specific panel regression model using nationwide county-level agriculture production data combined with fine-scale meteorological data, I primarily find the impact of a daily exposure to extreme temperatures on corn and soybean yields in the post-1996 period is 40% to 50% less than that in the pre-1996 period and the decline in the extreme temperature impacts on crop yields mainly occurs in counties with expanding irrigation coverage. Chapter 2 explores reasons for severe air pollution from the perspective of political economy by examining the environmental consequences of the county-to-city upgrading policy which delegates the autonomy of building cities to upgraded counties. In a centralized system like China, economic decentralization without changing the promotion metrics centered around economic performance for local government officials would likely lead to worse environmental quality because local officials compete for promotion on economic performance. Using a comprehensive county-level dataset on economic performance indicators and air pollutant concentrations, I primarily find significantly positive policy effects on economic growth and air pollutant concentrations, suggesting that the upgraded counties promoted economic performance at the cost of local air quality. I also calculate the total loss due to the increasing air pollution as valued in terms of statistical life to indicate the magnitude of the social cost of the upgrading policy. Following the finding of decline in agricultural sensitivity to extreme heat in Chapter 1, Chapter 3 quantifies the contribution of the temporal evolution of extreme temperature impacts to the growth of agricultural revenue during 1981-2010 using an Oaxaca-Blinder decomposition which attributes the growth of agricultural revenue to the change in the levels of predictors and to the change in the coefficients for the predictors. I find extreme temperature impacts on agricultural revenues per hectare in the post-1996 period is more than 60% lower than that in the pre-1996 period, contributing 6.1 percentage points of revenue growth over the two periods, which is 5.4% of the overall growth of agricultural revenue. The significant increase in marginal benefit of irrigation in terms of moderating extreme temperature impacts may have contributed about 40% of the decline in the extreme temperature impacts on agricultural revenue per hectare.

  • Open Access English
    Authors: 
    Biggs, Brenna;
    Publisher: eScholarship, University of California
    Country: United States

    Many California regulations try to decelerate climate change by mitigating emissions from various industries. Greenhouse gases (GHGs) such as methane, carbon dioxide, and nitrous oxide must be fully understood to meet these strict reduction goals. Landfills release GHGs during decomposition and active dumping, while dairy farms release GHGs enterically (i.e., from cows) and from manure management. This study aims to better understand these GHGs at active and closed Orange County landfills as well as at a Visalia dairy farm in California. All samples were collected using whole air sampling techniques and analyzed using gas chromatography to identify and quantify many trace gases. Select oxygenates (i.e., methanol, ethanol, and acetaldehyde), dimethyl sulfide, and carbonyl sulfide were also a focus at these locations. Unexpected and novel sources of these gases were revealed, which have possible implications for pollution and the global sulfur budget.Samples were collected at the landfills seasonally during four campaigns: Spring 2018, Summer 2018, Fall 2018, and Winter 2019 and at the dairy farm during five campaigns: September 2018, March 2019, June 2019, September 2019, and January 2020. Samples from both industries were compared to airborne and remote air samples to determine their enhancements relative to background concentrations. This research establishes previously unexplored or misrepresented sources of various gases, which is important for the success of the state’s reduction efforts, the environment, and the health of surrounding communities.California’s San Joaquin Valley, an extremely productive agricultural area, also contains many disadvantaged communities. Residents typically experience low socioeconomic status and a disproportionate amount of air pollution, which can lead to health problems. In addition to GHGs, this study also explores how direct emissions from dairy farms may affect these communities living downwind throughout the San Joaquin Valley. Orange County is more affluent but is often a nonattainment area for several pollutants including ozone and particulate matter, which affect the people living there. This study explores the contribution of trace gases from dairy farms and landfills in California to the formation of pollution and odor in these surrounding communities. Solutions for decreasing trace gas emissions from these sources are also proposed.

  • Open Access English
    Authors: 
    Li, Yin;
    Publisher: eScholarship, University of California
    Country: United States

    California Assembly Bill 32 (AB32) sets the goal to reduce greenhouse gas (GHG) emissions to a level 80% below 1990 levels by 2050. This deep decarbonization target requires major technology advancement and energy structure transition to a renewable and sustainable future. The environmental aspects of such a transition should be evaluated carefully before major investments in infrastructure are made. Biogas is a promising renewable energy resource in California that shares many similarities with natural gas but with the advantage of being carbon neutral since it generates energy from organic waste. However, biogas contains trace levels of numerous chemical compounds that depend on the feedstock and production process. The air quality implications of using biogas in different situations should be examined carefully before widespread adoption across California. The second chapter of this thesis characterizes the chemical and biological composition of raw biogas produced at five facilities using different feedstocks. The toxicity of combusted biogas is tested under fresh and photo-chemically aged conditions. Results find no strong evidence of potential occupational health risk from the five California biogas sites. Results also show no obvious differences between the toxicity of different biogas combustion exhaust after atmospheric dilution and aging. The third chapter of this thesis examines the emissions from the combustion of upgraded biogas that has CO2 removed and CH4 concentrated to be qualified as renewable natural gas (RNG). A light-duty cargo van was tested with CNG and two RNG blends on a chassis dynamometer to compare the toxicity of the resulting exhaust. CNG vehicle engine exhaust showed a higher or similar level of various toxicity responses, and photochemical reactions did not seem to alter the observed trend. These preliminary results suggest that utilizing biogas for direct heat and electricity generation or as vehicle fuel after upgrading could be useful strategies to reduce carbon intensity without negatively impacting air quality or public health. The fourth chapter of this thesis extends the scope by modeling air pollutant emissions from all California socio-economic sectors under different energy scenarios in the year 2050. To study the air quality implications of some key resources and technologies in the decarbonization transition, a total of six different scenarios were analyzed for various particulate and gaseous pollutant emissions. These scenarios include: 1) a business-as-usual future reference scenario "BAU", 2) a partial GHG reduction scenario that constrains only through 2030 with 40% reduction "CAP30", 3) a climate-friendly 80% GHG reduction scenario featuring deep penetration of advanced technologies and renewable energies "GHGAi", a same 80% GHG reduction scenario with the deployment of biomass carbon capture and sequestration technology "CCS", and two variation scenarios on GHGAi that examine the effect of using more natural gas in built environment "NGB" and power generation "NGT". Results show that major air quality benefits are expected from the GHGAi scenario, which includes aggressive decarbonization of electricity supply, electrification of most end-use appliances, improvement of appliances efficiency, and deployment of low-carbon transportation fuels and technologies. Bio-CCS technology holds promise as a shortcut to GHG mitigation and the utilization of natural gas bridges the transition from traditional to renewable energy systems, but neither of these technologies appear to be optimal from a future air quality management perspective. Adoption of biogas as an energy source plays a small but constructive role in the overall transition of California’s energy system towards a low carbon future.

  • Open Access English
    Authors: 
    Ebrahimi, Siavash;
    Publisher: eScholarship, University of California
    Country: United States

    Widespread electrification, i.e., switching direct fossil fuel end-uses to electricity, coupled with renewable power use is essential to achieve aggressive greenhouse gas and criteria pollutant emission reduction targets. Few have investigated the requisite electric grid infrastructure transformation and technology path coupled with spatial and temporal resolution of criteria pollutant emissions for assessing air quality impacts. In this study, we analyze grid and emission impacts of electrifying end-use sectors while decarbonizing power generation, using detailed modeling of infrastructure stocks and economic dispatch of the electric utility grid network. Results show that decarbonizing power supply by 50% without electrifying end-use sectors can reduce total California greenhouse gas emissions by only 2%, percent while partial electrification of end-use sectors alongside decarbonizing electricity generation by 50% yields up to 20.3 percent greenhouse gas emission reductions compared to 1990 levels. Spatially and temporally resolved criteria pollutant emissions portend certain scenarios that improve air quality more than others, requiring consideration of spatial and temporal emission perturbations dictated by specific electrification end-uses and power generation technology dynamics for meeting the increased electric demand. Combustion of fossil fuels for power generation, transportation, and other end-uses have resulted in significant air quality issues in urban areas. Solving this problem as well as climate change requires a holistic approach combining improved energy efficiency, cleaner power generation and electrification of fossil fuel end uses. However, the impact of this energy transition on local air quality has not been studied in detail. In this dissertation, we analyze the emissions and air quality impacts of electrifying end-use sectors while decarbonizing power generation, using detailed modeling of infrastructure stocks and economic dispatch of the electric grid. A set of scenarios are developed to study the impacts of electrification where each end-use sector is electrified based upon the electrification potential and feasibility of implementation using the available electric technologies. In order to accommodate higher statewide electricity demand due to electrification, the electricity generation sector is decarbonized through installing higher levels of renewable power. As electrifying energy end-uses affect the magnitude and temporal distribution of electric demand, we evaluate the amount of renewable energies that must be curtailed and quantify its implications for the load- balancing of electric grid system. High curtailment of renewable power under certain scenarios suggests the necessity for substantial energy storage to balance the grid dynamics and enable integration of higher levels of renewable power. Storing the excess renewable energy in form of hydrogen is a promising solution, which not only provides temporal electric grid balancing in matters of weeks to months, but also allows decarbonizing the transport sector. In the final chapter, we present a detailed control-oriented model for a PEM electrolyzer to characterize the dynamic response of the electrolysis platform in the time scale of minutes or seconds, which will enable us to investigate new control strategies for different grid services. The model is capable of characterizing PEM electrolyzer and essential for determining control strategy that will ensure efficient and reliable operation of the electrolyzer. Besides, the PEM electrolyzer dynamic model can be employed in the optimization of sustainable energy systems.

  • Open Access English
    Authors: 
    Soukup, James Vincent;
    Publisher: eScholarship, University of California
    Country: United States

    The San Pedro Bay Port Complex is a critical piece of the world economy as a hub of good movement and its activities generate significant pollutant emissions in an air basin that frequently struggles with degraded air quality. This research explores fuel cell deployment in place of diesel combustion engines for port activities and the air quality, GHG emissions, and human health impacts as a mitigation strategy for the degraded air quality induced by the ports. Fuel cell deployments are modeled as emission reductions in the year 2035 for port activities and ambient concentrations of air pollutants are obtained by simulating atmospheric chemistry (CMAQ). Ambient pollutant concentrations are compared against national standards and human health response functions from literature to assess impacts on morbidity and mortality as well as socioeconomics. Finally, Greenhouse Gas equivalency is determined for the emissions reductions modeled for the atmospheric simulation including upstream impacts associated with displaced diesel production and new hydrogen production. Results show potential for widespread reduction in ozone and fine particulate concentrations with titration-related increases in ozone at the immediate vicinity of the port. The maximum change in ozone was calculated to be a reduction of 5.09 ppb with a corresponding reduction in PM2.5 of 2.56 µg/m3 for the same case. Human health and socioeconomic modeling predict large net health and economic benefits. The valuation of health benefits is estimated to range $3,209,700 to $7,108,100 per day using modeling strategies demonstrated by the U.S. Environmental Protection Agency and California Air Resources Board.

  • Open Access English
    Authors: 
    Hausfather, Ezekiel Jon;
    Publisher: eScholarship, University of California
    Country: United States

    The observational temperature record is a critical part of our understanding of changes in Earth’s climate. However, large uncertainties remain in our historical measurements of surface, ocean, and atmospheric temperatures. Many of these are introduced by changes in measurement techniques over time, such as changing instrumentation, time of observation, or changes to the surrounding environment not representative of the broader region. Reducing these uncertainties is important to improve our understanding of long-term climate change, and has implications for assessing the magnitude of inter-decadal climate variability, evaluating the performance of climate models, determining the remaining carbon budget to achieve mitigation targets, among other issues. This dissertation is structured around four lead-authored papers that advance our understanding of the observational temperature record. The first paper, titled Quantifying the Effect of Urbanization on U.S. Historical Climatology Network Temperature Records, quantifies the extent to which changes in urban form surrounding measurement stations have biased long-term temperature records. By comparing temperature trends at urban and rural stations using four different proxy measures of urbanity, we find systematic differences between the raw (unadjusted) urban and rural temperature trends throughout the USHCN period of record. Based on these classifications, urbanization accounts for 14% to 21% of the rise in unadjusted minimum temperatures since 1895 and 6% to 9% since 1960. The homogenization process employed by NOAA effectively removes this urban signal such that it becomes insignificant during the last 50-80 years. In contrast, prior to 1930, only about half of the urban signal is removed. This suggests that biases in the land temperature record from urbanization are potentially significant, but can be effectively detected and removed when the network of observation stations is sufficiently dense to allow for neighbor-based pairwise homogenization.The second paper is titled Evaluating the Impact of U.S. Historical Climatology Network Homogenization Using the U.S. Climate Reference Network. In this paper the homogenization of surface temperature records in the U.S. is assessed by comparing the old weather station network (USHCN) to a new state-of-the-art U.S. Climate Reference Network (USCRN). The new U.S. Climate Reference Network provides a homogenous set of surface temperature observations that can serve as an effective empirical test of adjustments to raw USHCN stations. By comparing nearby pairs of USHCN and USCRN stations, we find that adjustments make both trends and monthly anomalies from USHCN stations much more similar to those of neighboring USCRN stations for the period from 2004-2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records. The third paper, titled Assessing Recent Warming Using Instrumentally Homogeneous sea Surface Temperature Records, seeks to solve a substantial disagreement between warming rates in different Sea surface temperature (SST) records over the past two decades. SST records are subject to potential biases due to changing instrumentation and measurement practices. Significant differences exist between commonly-used composite sea surface temperature reconstructions from NOAA’s Extended Reconstruction Sea Surface Temperature (ERSST), the Hadley Centre SST data set (HadSST3), and the Japanese Meteorological Agency’s Centennial Observation-Based Estimates of SSTs (COBE-SST) in recent years. The update from ERSST version 3b to version 4 resulted in an increase in the SST trend estimate during the last 18 years from 0.07°C/decade to 0.12°C/decade, indicating a higher rate of warming in recent years and eliminating some of the apparent “pause” in global surface temperatures over that period. We show that ERSST version 4 trends generally agree with largely-independent, near-global and instrumentally-homogeneous SST measurements from floating buoys, Argo floats, and radiometer-based satellite measurements that have been developed and deployed during the past two decades. We find a large cooling bias in ERSSTv3b and smaller but significant cooling biases in HadSST3 and COBE-SST from 2003 to present with respect to most series examined. These results suggest that reported rates of SST warming in recent years have been underestimated in these three datasets due to biases in ship-based measurements.The fourth paper, titled Evaluating the Performance of Past Climate Model Projections, looks at how well historical climate models published since 1970 have performed compared to observed temperature changes in the years after they were published. Climate models provide an important way to understand future changes in the Earth’s climate. Model projections rely on two things to accurately match observations: accurate modeling of climate physics, and accurate assumptions around future emissions of CO2 and other factors affecting the climate. The best physics-based model will still be inaccurate if it projects future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2 (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2 and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts, and increases our confidence that models are accurately projecting global warming.Work done in this dissertation has had a notable impact on our understanding and estimates of temperatures. This includes ensuring that urbanization is not biasing our record of land temperatures, testing the performance of land temperature homogenization, resolving differences between ocean temperature records in recent decades, developing a novel sea surface temperature record to help better understand WW2-era uncertainties, and evaluating recent changes in ocean heat content. In an encouraging sign of the impact of our work, the new HadSST4 temperature product from the UK Met Office prominently features comparisons with the instrumentally homogenous sea surface temperature records we developed.Similarly, the work that I and coauthors have undertaken has changed the approach used in evaluating the performance of GMST climate model projections, demonstrating the need to use common coverage and blended SAT/SST fields to ensure like-to-like comparisons with observations. Evaluating the future projections of old climate models improves our confidence that the current generation of models is accurately capturing the physical processes driving GMST change. This work on evaluating old climate models will be featured prominently in Chapter 1 of the IPCC 6th Assessment Report, where I serve as a contributing author.

  • Open Access English
    Authors: 
    Baxter, Ian;
    Publisher: eScholarship, University of California
    Country: United States

    Over the past 40 years the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflects a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic (hereafter referred to as the “Pacific-Arctic teleconnection (PARC)”), which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800-yr) CESM preindustrial simulation. These results further support the role of remote SST forcing originating from the tropical Pacific in exciting significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a Cold Pacific - Warm Arctic connection.

  • Open Access English
    Authors: 
    Forrest, Kate;
    Publisher: eScholarship, University of California
    Country: United States

    For California and other parts of the world to move towards a net-zero-emission grid, potentially a 100% renewable grid, complementary technologies to support renewable solar and wind integration need to be clearly established. Specifically, the integration of variable and intermittent solar and wind renewable generation requires resources that can respond dynamically to changes in the net load in order to ensure stable grid performance. Zero-emission vehicles (ZEVs), encompassing battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs), are uniquely positioned to (1) support variable renewable generation and provide benefits to the grid while, at the same time (2) reducing emissions from the transportation sector. Due to their disproportionately large contribution to air pollution and greenhouse gas (GHG) emissions, targeting heavy-duty vehicles (HDVs) is essential if reduction goals are to be met. This work assesses the feasibility of heavy duty ZEVs (HD-ZEVs), selecting California as the example. From a technical standpoint, more than half of Class 3-7 vehicle miles travelled (VMT) can be met with heavy-duty BEV product in development today without trip modification. Class 8 trucks have a much lower BEV feasibility due to their longer trip distances and heavy-duty FCEV product becomes more likely. The challenge becomes providing carbon-free fuel, namely renewable electricity for HD-BEVs, and renewable hydrogen for HD-FCEVs. This study assesses the fuel supply chain impact of HD-ZEV deployment on GHG emissions and air quality for the year 2050. HD-BEVs relying on uncoordinated charging can increase peak load demand and hinder the target of achieving zero GHG emissions from the electric grid. Intelligent charging of HD- BEVs and renewable hydrogen production for HD-FCEVs are both effective methods for utilizing otherwise curtailed renewable generation for the support of a zero or near-zero emissions electric grid. This study also finds that moving towards an 80% reduction in GHG emissions from HDVs through ZEV adoption has the co-benefit of significantly reducing ozone and PM2.5 concentrations in key regions of California. In comparison, reducing grid emissions from an 80% reduction to a 100% clean electric grid has a significantly smaller, but not trivial, impact in criteria air pollutant concentrations.

  • Open Access English
    Authors: 
    Caubel, Julien J;
    Publisher: eScholarship, University of California
    Country: United States

    Air pollution is one of the world’s greatest environmental health risks, responsible for over 7 million premature deaths annually. Around half of these premature mortalities are linked to biomass cooking fires that release harmful air pollutants into people’s homes, such as particulate matter (PM). Although nearly 3 billion people worldwide depend on biomass cooking fuels, relatively little scientific research exists on mitigating the smoke they generate. One promising approach for reducing emissions is the injection of secondary air into the biomass cookstove’s combustion chamber. However, cold secondary air can also quench the combustion process when improperly injected, and so many secondary air injection cookstove designs do not actually reduce harmful smoke emissions relative to a traditional three stone fire (TSF). Since wood is a common cooking fuel throughout the world, this dissertation presents an experimental wood-burning cookstove platform, dubbed the ‘Modular (MOD) stove’, to identify and optimize secondary air injection parameters that reduce the emission of harmful pollutants. The MOD stove enables systematic, repeatable experiments in which various secondary air injection design features, such as flow rate and location, can be quickly and easily adjusted. Over 130 experimental trials were conducted, demonstrating that wood combustion is highly sensitive to small changes in the secondary air injection parameters. Using a systematic experimental approach, an optimal design configuration was identified that reduces mass emissions of PM2.5, carbon monoxide (CO), and black carbon (BC) by ~90% relative to a traditional TSF, while also improving thermal efficiency. Using an updated version of the MOD stove, an additional 111 performance tests were conducted to quantify the practical design requirements (e.g., secondary air pressure and temperature) to achieve ≥ 90% mass emission reductions relative to a TSF. Using this experimental data, I demonstrate that low-cost (<$10) fans and blowers are currently available to drive the secondary flow, and this hardware can be independently powered using an inexpensive thermoelectric generator mounted nearby. Furthermore, size-resolved PM measurements demonstrate that secondary air injection effectively inhibits particle growth, but the total number of particles generated remains relatively unaffected. I investigate the potential impacts for human health and explore methods to mitigate the PM formation mechanisms that persist. As a whole, the MOD stove platform demonstrates that secondary air injection is a practical, effective, and potentially economical method for meaningfully reducing smoke emissions from biomass cookstoves. However, designs should be experimentally validated and optimized, and further research is needed to eliminate the persistent formation of ultrafine particles that are particularly harmful to human health. Ambient air pollution is also widespread, and linked to significant adverse health outcomes. Over 90% of the world’s population lives in areas where ambient air pollution concentrations exceed World Health Organization recommendations, resulting in ~4 million premature deaths annually. The health impacts of ambient air pollution are particularly acute in urban settings. In 2010, premature deaths due to ambient air pollution were about 50% more common in urban than in rural environments, and this could increase to nearly 90% by 2050. Although ground-based air quality measurements are needed to address this growing health crisis, traditional regulatory monitoring networks do not provide sufficient spatial coverage and resolution to adequately assess air pollution exposures in urban environments. Distributed networks of low-cost air quality sensors are emerging to fill this gap. Black carbon (BC) is an important component of PM pollution, strongly linked to adverse human health outcomes and climate change, but low-cost sensors for monitoring this critical pollutant are lacking. This dissertation presents the Aerosol Black Carbon Detector (ABCD), specifically designed for distributed air quality monitoring networks. As such, the ABCD integrates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, outdoor deployments. Most importantly, the ABCD incorporates a number of novel design features to provide uniquely accurate BC concentration measurements in tough operating environments that debilitate existing commercial instruments. Over 100 ABCDs were operated outdoors, and their measurement performance was comparable to that of a commercial BC instrument collocated inside a regulatory monitoring station. The validated fleet of ABCDs was deployed to 100 sampling sites in West Oakland, California – a neighborhood disproportionately affected by air pollution associated with the nearby Port of Oakland and surrounding highways. Over 100 days, the wireless sensor network successfully collected 84.0% of the 240,000 hourly BC concentration measurements desired (100 sampling sites × 2,400 hours). The widespread failure of miniature vacuum pumps was responsible for most missing measurements. The resulting BC concentration maps demonstrate that concentrations vary sharply over short distances (~100 m) and timespans (~1 hour), and generally depend on surrounding land use, traffic patterns, and location relative to prevailing winds. BC concentrations at each sampling site are highly repeatable over the diurnal and weekly cycles, and periodic trends are analyzed throughout the community. Using these trends as a reference, unusually polluted locations are detected, and likely emissions sources nearby are identified. In this way, the 100x100 Network demonstrates the value of low-cost sensor networks to accurately characterize urban air pollution distributions, and provide regulatory agencies, governments, and community stakeholders with actionable insights to mitigate the sources. Air pollution is a pervasive and persistent health threat that can only be tackled if we work to both mitigate and monitor emission sources. As such, the MOD stove studies presented here are targeted towards abating the world’s deadliest polluters. However, even the best of emissions reduction efforts are left blind without accurate measurements of the resulting air quality. The ABCD meets this need, providing accurate BC monitoring capabilities in a uniquely practical and economical package. Together, these complementary technologies will help underpin more comprehensive, data-driven efforts to quantifiably reduce harmful air pollution exposure throughout the world, and ultimately prevent millions of premature deaths.

  • Open Access English
    Authors: 
    Howard, Daniel Bost;
    Publisher: eScholarship, University of California
    Country: United States

    This dissertation proposes a methodology applicable worldwide to assess key health, climate and electricity system impacts of high penetrations of variable renewable energy (VRE), such as wind and solar energy, in the production of electricity. Three primary questions are addressed: (1) what are the health benefits and control costs of tightening emission standards for particulate matter (PM); (2) what are the health, climate and electricity grid impacts of high penetrations of VRE; and (3) is a 100% Renewable Portfolio Standard (RPS) electricity grid technically feasible in Northeast (NE) Brazil, and what are the associated health and climate benefits? The methodology I developed to answer these questions combines highly resolved spatial and temporal electricity grid simulation (via Plexos), atmospheric dispersion of power plant emissions (via CALPUFF), and human health impacts estimation (via BenMAP). The methodology is validated extensively over detailed case studies in NE Brazil, a region that has exceptionally high VRE and hydroelectric potential. Results for Question (1) indicate that when tightening emission standards, the health benefits outweigh the control costs by at least 50 times, even in a relatively clean region. Results for Question (2) show that health and climate benefits exceed US$267 million/yr and US$1.2 billion/yr respectively if NE Brazil transitions to a 45% VRE instead of a 30% VRE penetration in 2030. For Question (3), I find that a 100% RPS is not feasible using only wind, solar PV and hydroelectric resources in NE Brazil unless ~13% of demand can be flexibly imported and ~23% of generation can be flexibly exported; otherwise additional types of generation, storage and load balancing technology would need to be deployed. For this case, the health and climate benefits are at least US$433 million/yr and US$2.4 billion/yr respectively if NE Brazil transitions to a 100% RPS instead of a 30% VRE penetration in 2030.

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