Land carbon sensitivity to atmospheric CO2 concentration (bL) and climate warming (gL) is a crucial part of carbon-climate feedbacks that affect the magnitude of future warming. Although these sensitivities can be estimated by earth system models, their dependence on model representation of land carbon dynamics and the inherent model assumptions has rarely been investigated. Using the widely used Community Land Model version 4 as an example, we examine how bL and gL vary with prescribed versus dynamic vegetation covers. Both sensitivities are found to be larger with dynamic compared to prescribed vegetation on decadal timescale in the late twentieth century, with a more robust difference in gL. The latter is a result of dynamic vegetation model deficiencies in representing the competitions between deciduous versus evergreen trees and tree versus grass over the tropics and subtropics. The biased vegetation cover changes the regional characteristics of carbon-nitrogen cycles such that plant productivity responds less strongly to the enhancement of nitrogen mineralization with warming, so more carbon is lost to the atmosphere with rising temperature. The result calls for systematic evaluations of land carbon sensitivities with varying assumptions for land cover representations to help prioritize development effort and constrain uncertainties in carbon-climate feedbacks.

Emissions of greenhouse gases from the combustion of fossil fuels, in particular carbon dioxide (CO2), are a major contributor to global climate change. In the United States 28% of carbon dioxide emissions from fossil fuel combustion are produced by road vehicles. This dissertation reports the results of three studies that improve on our knowledge of the spatial and temporal distribution of vehicle CO2 emissions in the U.S. over the last 35 years. Using bottom-up data assimilation techniques we produce several new high-resolution inventories of vehicle emissions, and use these new data products to analyze the relationships between emissions, population, employment, traffic congestion, and climate change at multiple spatial and temporal scales across the U.S. We find that population density has a strong, non-linear effect on vehicle emissions, with increasing emissions in low density areas and decreasing emissions in high density areas. We identify large biases in estimates of vehicle CO2 emissions by the most commonly used national and global inventories, and highlight the susceptibility of spatially-downscaled inventories to local biases in urban areas. We also quantify emissions of several air pollutants regulated by the U.S. Environment Protection Agency, including carbon monoxide, nitrogen oxides and particulate matter, at hourly and roadway scales for the metropolitan area surrounding Boston, MA. Emissions of these pollutants show high emissions gradients across identifiable spatial hotspots, considerable diurnal and seasonal variations, and a high sensitivity to the presence or absence of heavy-duty truck traffic. We also find that the impact of traffic congestion on air pollution emissions across the region is minimal as a share of the total emissions. We show that policies that combine a reduction in the number of vehicles on the road with a focus on improving traffic speeds have greater success in reducing emissions of air pollutants and greenhouse gases than policies that focus solely on improving traffic speeds. Finally, we estimate that regional emissions of carbon monoxide will increase by 3% in 2050, but with numerous localized increases of 25-50%, due to an expected rise in mean regional temperatures due to global climate change.

Understanding the carbon cycle of major ecosystems is important in predicting feedback responses of the terrestrial biosphere to climate change. Bromus tectorum dominated ecosystems currently cover 7% of the Great Basin and represents a major land cover type for the region. This study looked at the carbon cycle of a near monoculture field of B. tectorum in southeastern Idaho, USA. A major portion of the study was dedicated to measurement validation because of the disagreement among techniques used to measure net ecosystem exchange (NEE) of CO2 between the atmosphere and terrestrial ecosystems . NEE, net photosynthesis, and canopy and soil respiration were quantified for the B. tectorum stand using multiple methods. This allowed for comparisons among measurement techniques and permitted the calculation of a best estimate of NEE. The study found that the eddy covariance technique underestimated NEE at night for the B. tectorum stand and the magnitude of underestimation increased with increasing leaf area index of the plant canopy. Annual NEE estimated by eddy covariance for the year 2005 was over four times lower than the best estimate of -80 g C m-2 yr-1 determined by a combination of methods. Implications are that many studies currently underestimate NEE and productive systems underestimate NEE more than less productive systems.

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Stem respiration is an important part of respiration coming from different dead and living stem tissues of trees, which makes an important contribution to the overall forest carbon balance. This report investigated spatial differences regarding radial diffusion of CO2 through the bark on trees across different old growth forests in Sweden. Some key environmental factors such as precipitation, wetness classes, temperature, stem diameter, distance from the coast, and latitude have been analysed to find relationships with stem respiration. Measurements were carried out on the most common tree species in Sweden, Pinus sylvestris, Picea abies and Betula pubescens. This was done by using a portable gas analyser strapped to the trees. The results show statistical differences in stem respiration for each tree species between some of the forests, while no statistical differences were found between wetness classes within or between forests. The only environmental factor that was found to have a significant relationship with stem respiration was stem diameter for P. sylvestris. Overall, these results indicate that stem respiration rate is relatively insensitive to environmental variation, which potentially simplifies the process of extrapolating this flux over space and time. Knowledge about stem respiration is important for understanding of the carbon cycle and prediction of future global change. Therefore, it is crucial to gain extensive information and understanding about the external relationships that could influence stem respiration.

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Thesis advisor: Hilary I. Palevsky / The biological carbon pump in the North Atlantic Ocean is powered by the annual spring phytoplankton bloom. These primary producers use inorganic carbon in the surface oceans and convert it into organic carbon, a fraction of which is exported out of the surface mixed layer and sequestered at depth. Determining the rate of carbon flux below the maximum winter mixed layer depth, driving sequestration on annual or longer timescales, is critical to understanding the North Atlantic carbon cycle.To constrain daily-to-annual scale changes in carbon export in the subpolar North Atlantic, I analyzed seven years of daily optical backscatter depth profiles (200-2600 m) collected from the subsurface profiler mooring at the Ocean Observatories Initiative (OOI)’s Global Irminger Sea Array from September 2014 to May 2021. This is the longest-running time series of daily, year-round optical backscatter profiles that has been collected in this region, providing novel opportunities to assess seasonal and interannual variations in particulate organic carbon (POC) flux to depth. This analysis, focused on large particles and aggregates identified from optical backscatter spikes, shows annual pulses of sinking particles initiating in May to June during each year of our seven-year time series, consistent with these export pulses being driven by organic matter production during the spring phytoplankton bloom. These pulses of particles sink through the water column at rates ranging from 10 and 30 meters per day, and though particle concentration attenuates through the water column due to remineralization, coherent large particle pulses generally extend deeper than 1500 m, the deepest maximum annual mixed layer depth over this period. Although deep winter mixing in this region requires sinking particles to penetrate much deeper than in other parts of the ocean to be sequestered long-term, pulses of large particles consistently penetrate to below even the deepest annual mixed layer depths in the region, highlighting the importance of these large particle pulses to carbon sequestration at depth in the subpolar North Atlantic. / Thesis (MS) — Boston College, 2024. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Earth and Environmental Sciences.

Managed loblolly pine forests comprise an important pool in the global carbon cycle. Understanding the influences upon inputs and outputs of this pool, including the effects of management activities, will allow landowners to understand how carbon can be sequestered in their stands. Specific to this study, we sought to create multivariate models of the output of carbon from the soil in the form of soil CO2 efflux (Rs) and a component of that total efflux, heterotrophic respiration index (Rh), from data collected across the managed range of loblolly pine in the Southeastern U.S. We also performed tests of significance on controlled subsets of these data for the effects of fertilization and of thinning. Finally, we sought a connection between stand leaf area index (LAI) and total soil CO2 efflux or heterotrophic respiration. Our models indicated variability in both Rs and Rh across latitude and physiographic province, respectively, within this range. The Rs (R2 = 0.56) model included temperature, latitude, a soil moisture by temperature effect, soil nitrogen, and bulk density variables. The Rh (R2 = 0.50) model included soil moisture, a temperature by moisture interaction, and physiographic province. Rs was not significantly affected by either fertilization or thinning, yet Rh was influenced by both (negatively and positively, respectively). This indicates a shift in relative contributions of heterotrophic respiration and root respiration components to Rs in response to these treatments. Heterotrophic respiration was shown to have a weak negative response (R2 = 0.04) to increasing stand LAI. / Master of Science