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The detoxification process mediated by carboxylic acids (CAs) has received considerable spotlights since CAs are clean reagent and ubiquitous in the natural environments and effluents. Here, we present an exhaustive review on surface-bound/dissolved metals-catalyzed Cr(VI) reduction by CAs and CAs-mediated Cr(VI) reduction by many highly/poorly reductive reagents. The overall mechanisms of Cr(VI) reduction are mainly associated with the coordination of CAs with surface-bound/dissolved metals or Cr(VI,V,IV) species and the electron donating abilities of CAs. Additionally, the general decays of intermediate Cr(V,IV) complexes are clearly emerged in the Cr(VI) reduction processes. The performance of various reaction systems for Cr(VI) reduction that is greatly dependent on the operation parameters, including solution pH, reagent concentration, temperature, coexisting ions and gas atmosphere, are also critically commented. From the study survey presented herein, CAs-mediated Cr(VI) reduction processes exhibit good potential for remediation of various Cr(VI)-contaminated waters/sites. However, there is still a need to address the remained bottle-necks and challenges for the remediation of Cr(VI) mediated by CAs in the related natural attenuation cases and the treatment of industrial effluents. Overall, the present review offers the comprehensive understanding of the Cr(VI) reduction mediated by CAs and provide the engineering community with the guidelines for Cr(VI) remediation in the real-world applications.

Published online: 19 January, 2021 Unique longitudinal probabilistic expectations data from the Berea Panel Study, which cover both the college and early post-college periods, are used to examine young adults’ beliefs about their future incomes. We introduce a new measure of the ex post accuracy of beliefs, and two new approaches to testing whether, ex ante, agents exhibit Rational Expectations. We show that taking into account the additional information about higher moments of individual belief distributions contained in probabilistic expectations data is important for detecting types of violations of Rational Expectations that are not detectable by existing mean-based tests. Beliefs about future income are found to become more accurate as students progress through school and then enter the post-college period. Tests of Rational Expectations almost always reject for the in-school period, but the evidence against Rational Expectations is much weaker in the post-college period.

The fundamental importance of beliefs about future outcomes in decision-making suggests that an accurate characterization of these beliefs is important for understanding individuals' behavior and for evaluating the counterfactuals typically needed for policy analysis. Traditionally, many researchers have been using some form of Rational Expectations (RE) assumptions to characterize these beliefs. However, empirical evidence suggests that the RE assumption might not hold in many contexts, and that incorrectly imposing the RE assumption can lead to biased policy predictions. Motivated by these findings, I explore alternative approaches to conducting economic analysis without imposing the RE assumption. Chapters 2 and 3 of my thesis, which are co-authored with Todd and Ralph Stinebrickner, utilize unique survey expectations data from the Berea Panel Study (BPS) to characterize college students' beliefs about various future outcomes. Specifically, in Chapter 2, we characterize how much uncertainty about post-college income is present for students at college entrance and how quickly this uncertainty is resolved. Measuring an individual's income uncertainty by the variance of the distribution describing her beliefs about earnings at age 28, we find that, on average, students resolve roughly one-third of the income uncertainty present at the time of entrance during college. Consistent with the finding that the majority of initial income uncertainty remains at the end of college, We find that uncertainty about college GPA and field of study, which are the two primary income-influencing factors that are realized in college, can only account for about 19% to 27% of students' initial income uncertainty. Chapter 3 provides a concrete example that illustrates the importance of quantifying the resolution of students' (income) uncertainty during college. By entering college, students have the option to decide whether to remain in college after receiving relevant new information. We show that the value of this option of receiving new information is determined by a student's dropout probability and how much uncertainty is resolved before the decision is made. Taking advantage of longitudinal expectations data from the BPS, we find that students have accurate perceptions about the amount of income uncertainty that is resolved during college but vastly underestimate the probability of dropping out of school. Consequently, on average, they underestimate this option value by 65%. Chapter 4 proposes an alternative, model-based approach to jointly nonparametrically identify individuals' beliefs and the decision rule, which is a function that maps beliefs to decisions. My method can be applied to signal-based learning models, where individuals use signals to update their beliefs about an unknown permanent factor and repeatedly make decisions based on these beliefs. The econometrician observes individuals' decisions and the signals they receive at each period. Using data from the BPS, I apply my method to estimate the relationship between college students' study time and their beliefs about academic productivity as measured by the ratio of semester GPA to study time. I find that expectations about own academic productivity have a negative effect on study time. The RE assumption is rejected at a 10% level for a subgroup of students. Incorrectly imposing the RE assumption would lead to a substantially larger estimate of the effect of expectations about academic productivity on college study time.

While a large literature is interested in the relationship between family and labor supply outcomes, little is known about the expectations of these objects at earlier stages. We examine these expectations, taking advantage of unique data from the Berea Panel Study. In addition to characterizing expectations, starting during college, the data details outcomes for ten years after graduation. Methodological contributions come from approaches to validate quality of survey expectations data and the recognition that expectations data, along with longitudinal data, can potentially help address endogeneity issues arising in the estimation of the causal effect of family on labor supply.

An important feature of post-secondary schooling is the experimentation that accompanies sequential decision-making. Specifically, by entering college, a student gains the option to decide at a future time whether it is optimal to remain in college or to drop out, after resolving uncertainty that existed at entrance about factors that affect the return to college. This paper uses data from the Berea Panel Study to quantify the value of this option. The unique nature of the data allows us to make a distinction between "actual" option values and "perceived" option values and to examine the accuracy of students' perceptions. We find that the average perceived option value is 65% smaller than the average actual option value ($8,670 versus $25,040). A further investigation suggests that this understatement is not due to misperceptions about how much uncertainty is resolved during college, but, rather, because of overoptimism at entrance about the returns to college. In terms of policy implications related to college entrance, we do not find evidence that students understate the overall value of college, which depends on the sum of the option value and expectations at entrance about the returns to college.