Understanding China's climate change mitigation policy development: Structures, processes and outcomes

Climate change is one of the most important and urgent issues of our time. Since 2006, China has overtaken the United States as the world’s largest greenhouse gas (GHG) emitter. China’s role in an international climate change solution has gained increased attention. Although much literature has addressed the functioning, performance, and implications of existing climate change mitigation policies and actions in China, there is insufficient literature that illuminates how the national climate change mitigation policies have been formulated and shaped. This research utilizes the policy network approach to explore China’s climate change mitigation policy making by examining how a variety of government, business, and civil society actors have formed networks to address environmental contexts and influence the policy outcomes and changes. The study is qualitative in nature. Three cases are selected to illustrate structural and interactive features of the specific policy network settings in shaping different policy arrangements and influencing the outcomes in the Chinese context. The three cases include the regulatory evolution of China’s climate change policy making; the country’s involvement in the Clean Development Mechanism (CDM) activity, and China’s exploration of voluntary agreement through adopting the Top-1000 Industrial Energy Conservation Program. The historical analysis of the policy process uses both primary data from interviews and fieldwork, and secondary data from relevant literature. The study finds that the Chinese central government dominates domestic climate change policy making; however, expanded action networks that involve actors at all levels have emerged in correspondence to diverse climate mitigation policy arrangements. The improved openness and accessibility of climate change policy network have contributed to its proactive engagement in promoting mitigation outcomes. In conclusion, the research suggests that the policy network approach provides a useful tool for studying China’s climate change policy making process. The involvement of various types of state and non-state actors has shaped new relations and affected the policy outcomes and changes. In addition, through the cross-case analysis, the study challenges the “fragmented authoritarianism” model and argues that this once-influential model is not appropriate in explaining new development and changes of policy making processes in contemporary China.

Cognitive competence and life course change in multi-problem adolescents

The dissertation reports on two studies. The purpose of Study I was to develop and evaluate a measure of cognitive competence (the Critical Problem Solving Skills Scale – Qualitative Extension) using Relational Data Analysis (RDA) with a multi-ethnic, adolescent sample. My study builds on previous work that has been conducted to provide evidence for the reliability and validity of the RDA framework in evaluating youth development programs (Kurtines et al., 2008). Inter-coder percent agreement among the TOC and TCC coders for each of the category levels was moderate to high, with a range of .76 to .94. The Fleiss' kappa across all category levels was from substantial agreement to almost perfect agreement, with a range of .72 to .91. The correlation between the TOC and the TCC demonstrated medium to high correlation, with a range of r(40)=.68, p<.001 to r(40)=.79, p<.001. Study II reports an investigation of a positive youth development program using an Outcome Mediation Cascade (OMC) evaluation model, an integrated model for evaluating the empirical intersection between intervention and developmental processes. The Changing Lives Program (CLP) is a community supported positive youth development intervention implemented in a practice setting as a selective/indicated program for multi-ethnic, multi-problem at risk youth in urban alternative high schools in the Miami Dade County Public Schools (M-DCPS). The 259 participants for this study were drawn from the CLP's archival data file. The study used a structural equation modeling approach to construct and evaluate the hypothesized model. Findings indicated that the hypothesized model fit the data (χ2 (7) = 5.651, p = .83; RMSEA = .00; CFI = 1.00; WRMR = .319). My study built on previous research using the OMC evaluation model (Eichas, 2010), and the findings are consistent with the hypothesis that in addition to having effects on targeted positive outcomes, PYD interventions are likely to have progressive cascading effects on untargeted problem outcomes that operate through effects on positive outcomes.

Development of New Structural Health Monitoring Techniques

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Development of New Structural Health Monitoring Techniques

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Effects of in situ CO2 enrichment on structural characteristics, photosynthesis, and growth of the Mediterranean seagrass Posidonia oceanica

Seagrass is expected to benefit from increased carbon availability under future ocean acidification. This hypothesis has been little tested by in situ manipulation. To test for ocean acidification effects on seagrass meadows under controlled CO2/pH conditions, we used a Free Ocean Carbon Dioxide Enrichment (FOCE) system which allows for the manipulation of pH as continuous offset from ambient. It was deployed in a Posidonia oceanica meadow at 11 m depth in the Northwestern Mediterranean Sea. It consisted of two benthic enclosures, an experimental and a control unit both 1.7 m**3, and an additional reference plot in the ambient environment (2 m**2) to account for structural artifacts. The meadow was monitored from April to November 2014. The pH of the experimental enclosure was lowered by 0.26 pH units for the second half of the 8-month study. The greatest magnitude of change in P. oceanica leaf biometrics, photosynthesis, and leaf growth accompanied seasonal changes recorded in the environment and values were similar between the two enclosures. Leaf thickness may change in response to lower pH but this requires further testing. Results are congruent with other short-term and natural studies that have investigated the response of P. oceanica over a wide range of pH. They suggest any benefit from ocean acidification, over the next century (at a pH of 7.7 on the total scale), on Posidonia physiology and growth may be minimal and difficult to detect without increased replication or longer experimental duration. The limited stimulation, which did not surpass any enclosure or seasonal effect, casts doubts on speculations that elevated CO2 would confer resistance to thermal stress and increase the buffering capacity of meadows.

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

Medium change monitoring using ambient seismic noise and coda wave interferometry: examples from intraplate NE Brazil and the Mid-Atlantic Ridge

This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake’s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers’ amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault’s region induced by the earthquake.

Encapsulation of phase change materials using rice-husk-char

This paper explored a new approach to prepare phase change microcapsules using carbon-based particles via Pickering emulsions for energy storage applications. Rice-husk-char, a by-product in biofuel production, containing 53.58 wt% of carbon was used as a model carbon-based material to encapsulate hexadecane. As a model phase change material, hexadecane was emulsified in aqueous suspensions of rice-husk-char nanoparticles. Water soluble polymers poly(diallyldimethyl-ammonium chloride) and poly(sodium styrene sulfonate) were used to fix the rice-husk-char nanoparticles on the emulsion droplets through layer-by-layer assembly to enhance the structural stability of the microcapsules. The microcapsules formed are composed of a thin shell encompassing a large core consisting of hexadecane. Thermal gravimetrical and differential scanning calorimeter analyses showed the phase change enthalpy of 80.9 kJ kg−1 or 120.0 MJ m−3. Design criteria of phase change microcapsules and preparation considerations were discussed in terms of desired applications. This work demonstrated possible utilisations of biomass-originated carbon-based material for thermal energy recovery and storage applications, which can be a new route of carbon capture and utilisation.

Structural and functional vulnerability to elevated pCO2 in marine benthic communities

The effect of elevated pCO2/low pH on marine invertebrate benthic biodiversity, community structure and selected functional responses which underpin ecosystem services (such as community production and calcification) was tested in a medium-term (30 days) mesocosm experiment in June 2010. Standardised intertidal macrobenthic communities, collected (50.3567°N, 4.1277°W) using artificial substrate units (ASUs), were exposed to one of seven pH treatments (8.05, 7.8. 7.6, 7.4, 7.2, 6.8 and 6.0). Community net calcification/dissolution rates, as well as changes in biomass, community structure and diversity, were measured at the end of the experimental period. Communities showed significant changes in structure and reduced diversity in response to reduced pH: shifting from a community dominated by calcareous organisms to one dominated by non-calcareous organisms around either pH 7.2 (number of individuals and species) or pH 7.8 (biomass). These results were supported by a reduced total weight of CaCO3 structures in all major taxa at lowered pH and a switch from net calcification to net dissolution around pH 7.4 (Omega calc = 0.78, Omega ara = 0.5). Overall community soft tissue biomass did not change with pH and high mortality was observed only at pH 6.0, although molluscs and arthropods showed significant decreases in soft tissue. This study supports and refines previous findings on how elevated pCO2 can induce changes in marine biodiversity, underlined by differential vulnerability of different phyla. In addition, it shows significant elevated pCO2-/low pH-dependent changes in fundamental community functional responses underpinning changes in ecosystem services.

Seawater carbonate chemistry and structural integrity of the coralline algae Lithothamnion glaciale in a laboratory experiment

The uptake of anthropogenic emission of carbon dioxide is resulting in a lowering of the carbonate saturation state and a drop in ocean pH. Understanding how marine calcifying organisms such as coralline algae may acclimatize to ocean acidification is important to understand their survival over the coming century. We present the first long-term perturbation experiment on the cold-water coralline algae, which are important marine calcifiers in the benthic ecosystems particularly at the higher latitudes. Lithothamnion glaciale, after three months incubation, continued to calcify even in undersaturated conditions with a significant trend towards lower growth rates with increasing pCO2. However, the major changes in the ultra-structure occur by 589 µatm (i.e. in saturated waters). Finite element models of the algae grown at these heightened levels show an increase in the total strain energy of nearly an order of magnitude and an uneven distribution of the stress inside the skeleton when subjected to similar loads as algae grown at ambient levels. This weakening of the structure is likely to reduce the ability of the alga to resist boring by predators and wave energy with severe consequences to the benthic community structure in the immediate future (50 years).

Effects of introspection on meta and structural attitude bases

Introspection is the process by which individuals question their attitudes; either questioning why they hold their attitudes (Why introspection), or how they feel about a particular attitude object (How introspection). Previous research has suggested that Why-introspection induces attitude change, and that Why and How introspection influence attitude-behaviour consistency,persuasion, and other effects. Generally, psychologists have assumed that affective and cognitive attitude bases are the mechanism by which introspection leads to these effects. Leading perspectives originating from these findings suggest that either Why introspection changes the content of cognitive attitude bases (the skewness hypothesis), or increases the salience of cognitive attitude bases (the dominance hypothesis); whereas How introspection may increase the salience of affective attitude bases (another part of the dominance hypothesis). However, direct evidence for these mechanisms is lacking, and the distinction between structural and meta bases has not been considered. Two studies investigated this gap in the existing literature. Both studies measured undergraduate students’ attitudes and attitude bases (both structural and meta, affective and cognitive) before and after engaging in an introspection manipulation (Why introspection / How introspection / control), and after reading a (affective / cognitive) persuasive passage about the attitude object. No evidence was found supporting either the skewness or dominance hypotheses. Furthermore, previous introspection effects were not replicated in the present data. Possible reasons for these null findings are proposed, and several unexpected effects are examined.

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.

Encapsulation of phase change materials using rice-husk-char

This paper explored a new approach to prepare phase change microcapsules using carbon-based particles via Pickering emulsions for energy storage applications. Rice-husk-char, a by-product in biofuel production, containing 53.58 wt% of carbon was used as a model carbon-based material to encapsulate hexadecane. As a model phase change material, hexadecane was emulsified in aqueous suspensions of rice-husk-char nanoparticles. Water soluble polymers poly(diallyldimethyl-ammonium chloride) and poly(sodium styrene sulfonate) were used to fix the rice-husk-char nanoparticles on the emulsion droplets through layer-by-layer assembly to enhance the structural stability of the microcapsules. The microcapsules formed are composed of a thin shell encompassing a large core consisting of hexadecane. Thermal gravimetrical and differential scanning calorimeter analyses showed the phase change enthalpy of 80.9 kJ kg−1 or 120.0 MJ m−3. Design criteria of phase change microcapsules and preparation considerations were discussed in terms of desired applications. This work demonstrated possible utilisations of biomass-originated carbon-based material for thermal energy recovery and storage applications, which can be a new route of carbon capture and utilisation.

Asymptotic Change-Point Analysis of the Dependencies in Time Series

In recent papers, Wied and his coauthors have introduced change-point procedures to detect and estimate structural breaks in the correlation between time series. To prove the asymptotic distribution of the test statistic and stopping time as well as the change-point estimation rate, they use an extended functional Delta method and assume nearly constant expectations and variances of the time series. In this thesis, we allow asymptotically infinitely many structural breaks in the means and variances of the time series. For this setting, we present test statistics and stopping times which are used to determine whether or not the correlation between two time series is and stays constant, respectively. Additionally, we consider estimates for change-points in the correlations. The employed nonparametric statistics depend on the means and variances. These (nuisance) parameters are replaced by estimates in the course of this thesis. We avoid assuming a fixed form of these estimates but rather we use "blackbox" estimates, i.e. we derive results under assumptions that these estimates fulfill. These results are supplement with examples. This thesis is organized in seven sections. In Section 1, we motivate the issue and present the mathematical model. In Section 2, we consider a posteriori and sequential testing procedures, and investigate convergence rates for change-point estimation, always assuming that the means and the variances of the time series are known. In the following sections, the assumptions of known means and variances are relaxed. In Section 3, we present the assumptions for the mean and variance estimates that we will use for the mean in Section 4, for the variance in Section 5, and for both parameters in Section 6. Finally, in Section 7, a simulation study illustrates the finite sample behaviors of some testing procedures and estimates.

Structural Time Series Modeling: an Application to Environmental Variables

A structural time series model is one which is set up in terms of components which have a direct interpretation. In this paper, the discussion focuses on the dynamic modeling procedure based on the state space approach (associated to the Kalman filter), in the context of surface water quality monitoring, in order to analyze and evaluate the temporal evolution of the environmental variables, and thus identify trends or possible changes in water quality (change point detection). The approach is applied to environmental time series: time series of surface water quality variables in a river basin. The statistical modeling procedure is applied to monthly values of physico- chemical variables measured in a network of 8 water monitoring sites over a 15-year period (1999-2014) in the River Ave hydrological basin located in the Northwest region of Portugal.