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The price of carbonwashing: market responses to carbon disclosure controversies
(Emerald, 2026-07-01) ElAlfy, Amr; Nassar, Mohamed; Quigley, John; Tang, Leilei
Purpose: This study examines whether capital markets penalize firms for carbonwashing-related controversies and under what conditions such penalties occur. Specifically, it investigates how the visibility of carbonwashing incidents influences investor reactions to misleading or selective corporate disclosure of greenhouse gas (GHG) emissions. Design/methodology/approach: Using a dataset of climate-related controversies identified by RepRisk, the study analyzes short-term stock market reactions for S&P 500 firms over the period 2010–2023. A standard market-model event study is employed to estimate cumulative abnormal returns (CARs) over a [−2,+2] event window. The analysis is complemented by non-parametric tests and panel regressions with firm and time fixed effects. Grounded in signaling theory, corporate climate disclosures are conceptualized as signals of environmental commitment, while carbonwashing incidents are treated as negative signals that undermine signal credibility. Findings: The results show that capital markets do not uniformly penalize climate-related controversies. Negative stock price reactions are concentrated in carbonwashing incidents that receive substantial media attention. High-visibility GHG-related controversies are associated with significantly lower cumulative abnormal returns and greater downside risk, whereas low-visibility incidents generate muted market responses. These findings suggest that carbonwashing becomes financially material primarily when negative signals are widely disseminated and perceived as credible by investors. Although the analysis focuses on US-listed S&P 500 firms, the findings establish a baseline for how large-cap markets price carbonwashing. They also point to the European regulatory environment, particularly the mandatory assurance provisions under the corporate sustainability reporting directive (CSRD), as a natural setting for cross-jurisdictional replication, where stricter frameworks increase both the visibility and financial materiality of carbon disclosure practices. Research limitations/implications: The analysis focuses on short-term market reactions and relies on controversies identified in the RepRisk database, which may not capture all instances of misleading climate disclosure. Nevertheless, the findings highlight the importance of transparency and signal credibility in climate-related corporate communication. They also suggest that investor responses depend strongly on the information environment surrounding sustainability controversies. These implications are especially salient for European firms operating under enhanced disclosure and assurance requirements, where credibility risks are likely to be more tightly scrutinized. Originality/value: This study contributes to the sustainability and corporate strategy literature by showing that the financial consequences of carbonwashing depend on the visibility and credibility of negative signals rather than the mere existence of misleading climate communication. The results provide insights for managers, investors and policymakers seeking to strengthen the credibility of climate disclosure in capital markets.
Polymeric Gas Sensing Materials for Detection of Toxic Analytes
(University of Waterloo, 2026-07-10) Mavani, Bhoomi
Toxic volatile organic compounds (VOCs), including formaldehyde, are pervasive in both industrial and indoor environments and pose serious health risks at even low chronic exposure levels, yet the tools available for real-time monitoring remain bulky, expensive, and ill-suited for portable or wearable deployment. At its core, this is majorly a materials problem and no potential transducer architecture in a micro gas sensor can compensate enough for a sensing layer that lacks the chemical specificity to distinguish formaldehyde from structurally similar interferents like ethanol, acetone, and benzene. This thesis approaches this materials challenge directly, tracing a systematic path from backbone chemistry through composite engineering and regeneration characterization to device-level integration, with the goal of understanding not just which materials work but why they work and how that understanding can guide rational design of gas sensing polymeric materials for any gas analyte. Four pristine conducting polymer backbones were first screened under single-gas and multi-component gas exposures. Polyaniline (PANI) and poly(2,5-dimethylaniline) (P25DMA) emerged as the most promising candidates. Under quaternary mixture conditions (formaldehyde, ethanol, acetone, and benzene at 2 ppm each), P25DMA was the only pristine material to exceed a mixture selectivity index F/(E+A+B) value of ~1.02 compared to ~0.59 for PANI, attributable to the steric and electronic influence of the dimethyl ring substitution reducing non-selective hydrogen-bonding with competing oxygenates. However, even P25DMA's selectivity advantage has limits and neither backbone alone provides the sensitivity-selectivity combination required for robust real-world deployment. This established the case for composite modification: not as an incremental improvement, but as a necessary step to access adsorption environments that pristine polymer chemistry alone cannot deliver. To further improve performance, metal oxides (In2O3, NiO, SnO2, TiO2) were incorporated into both backbones. The central finding is that metal oxide identity governs the mode of incorporation, which in turn dictates pore architecture and ultimately drives sensitivity and selectivity outcomes. Because APS-initiated polymerization occurs in a strongly acidic medium, each metal oxide's resistance to dissolution during synthesis determines whether it survives as a surface-accessible particle or becomes buried within the polymer matrix. In2O3 and SnO2, being acid-stable, remain particulate and expose hydroxylated, defect-rich surfaces whose polar adsorption sites interact preferentially with formaldehyde's carbonyl group, simultaneously enhancing sensitivity and maintaining selectivity. NiO, being acid-labile, becomes polymer-encased during synthesis and contributes no chemically differentiated surface, instead blocking active amine sites at higher loadings and degrading selectivity precisely where sensitivity appears to peak. This acid stability explains why metal oxide identity matters relatively more than metal oxide loading as a first design variable. Backbone architecture then determines how effectively that oxide can be dispersed: P25DMA's lamellar structure anchors 3.6 times more In2O3 than PANI's fibrillar network under the same recipe, generating a denser polymer-metal oxide interfacial perimeter where selective adsorption events occur. Pore accessibility completes the picture by controlling whether analyte molecules can physically reach those interfacial sites and whether the pore environment favors selective or non-selective uptake. At the optimal 5% In2O3 loading in P25DMA, confinement-dominated transport gives way to open, externally accessible surface where formaldehyde's smaller kinetic diameter and stronger affinity for oxide sites gives it a systematic competitive advantage over interferents, driving sensitivity and selectivity simultaneously. This hierarchy, from metal oxide acid stability to embedding mode to backbone morphology to pore accessibility to competitive adsorption selectivity, is not specific to formaldehyde and provides a transferable framework for designing polymer-oxide composites toward any analyte where backbone-analyte affinity and metal oxide surface chemistry can be deliberately matched. Finally, both pristine P25DMA and P25DMA with 5% In2O3 composite were deposited onto a MEMS resonant mass sensor. Formaldehyde exposure of the functionalized MEMS sensor displayed device-level transduction of polymer sorption, with P25DMA with 5% In2O3 composite exhibiting larger and faster frequency shifts than the pristine P25DMA. This is in agreement with and reinforces the observation of improved sensing performance of the composite material. For a sensing material to be practically deployable, sensitivity and selectivity alone are not enough: it must also recover reliably after exposure and survive repeated use without structural degradation. PANI regenerates through mild thermal assistance up to 80°C enhances desorption kinetics without compromising backbone integrity. Beyond this point, the onset of glass transition induces segmental mobility that shortens analyte residence time and reduces retained analyte in polymer matrix leading to desorption. The post-regeneration characterization confirms the backbone remains chemically intact throughout, establishing that the material can be returned to baseline under mild conditions without sacrificing the chemical properties that drive its sensing performance. Additional parametric studies on synthesis temperature, ageing, sensing layer mass, physical form, and carbon-based fillers collectively confirmed that composition-driven effects from oxide identity and loading are the dominant levers for tuning selectivity, while processing variables impose secondary but measurable influences. Underpinning all of this materials work is a detailed mechanistic and kinetic study of PANI polymerization itself, tracing the initiation, chain growth, and termination steps and developing a numerical kinetic model that predicts monomer conversion and molecular weight evolution, ensuring that the sensing materials produced in this thesis are understood at the level of their synthesis chemistry rather than treated as empirical outputs. Taken together, this thesis demonstrates that the path to high-performance polymer-based formaldehyde sensing runs through a hierarchy of materials decisions, from backbone chemistry through oxide acid stability and embedding mode to pore architecture, and that mechanistic understanding of each step is what enables co-optimization of sensitivity, selectivity, and renderability rather than trading one against another.
Scalable Program Analysis: Abstract Interpretation Techniques and Practical Applications
(University of Waterloo, 2026-07-10) Su, Yusen
Static program analysis aims to infer how a program behaves by reasoning about its source code under a formal semantics, without executing it. It is a core technique for software verification, compiler optimization, and security analysis; key applications include establishing memory safety guarantees, inferring numerical invariants, and detecting unsafe information flows. A central challenge is the precision--scalability trade-off: coarse abstractions scale but generate many false alarms, while highly precise methods often struggle on large codebases. This thesis develops sound and automated static analyses in the context of abstract interpretation, to achieve sufficient precision for formal verification while maintaining scalability on practical verification tasks. The thesis presents three contributions. First, for memory safety verification, which requires inferring invariants to prove the validity of spatial memory accesses (i.e., that accessed buffer offsets remain within the bounds of their allocated buffer), we build a new abstract domain for reasoning about object invariants, where memory objects sharing common properties are abstracted relationally (i.e., summarized into a single abstract representation). However, such summarization causes precision loss when the properties of the summarized objects are temporarily violated during updates. To mitigate this, we introduce a new memory abstraction that separates recently manipulated objects from unchanged objects (i.e., summary objects). The new domain combines simpler subdomains for objects and scalars, so each part stays small and the whole analysis scales; the parts then exchange information through domain reduction to recover the precision that splitting them would otherwise lose. Second, for inferring numerical invariants, we propose a new numerical domain, Template Difference-Bounded Matrices (tDBM), to capture a useful subset of Two Variable Per Inequality (TVPI) constraints needed for bounds checking. By extending the matrix with additional dimensions via ghost variables that represent variables with scaled coefficients, tDBM provides a practical middle ground between lightweight weakly relational domains and expensive fully relational domains. Third, for information-flow security, we present a field-sensitive taint analysis that combines pointer analysis and data-flow analysis, and further integrates abstract-interpretation-based value reasoning to prune infeasible flows and reduce false positives. To improve precision in heap reasoning, we also introduce a refined variant of pointer analysis that better preserves field sensitivity while retaining scalability. Overall, this thesis develops abstract domains tailored to the property being verified and kept lightweight without sacrificing the precision each task needs. Together, they prove memory safety and information-flow security while scaling to real-world programs.
Inverse Design and Lithographic Pattern Transfer of a Thin Near-Infrared All-Silicon Absorber
(University of Waterloo, 2026-07-09) Roy, Lucas
All-silicon photodetectors are seldom used for Near-Infrared (NIR) Light Detection and Ranging (LiDAR) due to the low absorption coefficient of silicon in the NIR wavelength range. The absorptance of the absorption region is typically increased by increasing the depth of the absorption region, however, this approach adds timing jitter to a photode- tector that can severely limit the ranging resolution of the LiDAR system. This work maximized the absorptance of a silicon absorber in a fixed-depth 2.475 μm absorption re- gion from a theoretical baseline value of 2.58% to a simulated value of 8.33% for 950 nm wavelength incident light, a more than 3-fold improvement. The simulated absorptance enhancement compared to the baseline value was 3.2, whereas perfect black silicon only displays an absorptance enhancement of less than 1.5 at the 950 nm wavelength, giving the structure designed and simulated in this work a more than 2-fold absorptance enhancement improvement over perfect black silicon. This work applied topological optimization and inverse design methodologies to gen- erate the unique all-silicon 2 μm by 2 μm meta-atom absorber with vertical sidewalls. A pattern transfer using electron-beam lithography on a planar silicon sample with 340 nm of ZEP520A resist was conducted as a proof of concept that the pattern can be transferred faithfully into a real silicon sample. At the time that this work was conducted, the author was unaware of any such studies that applied topological optimization to maximize the absorptance of a thin all-silicon NIR absorber. This work showed that topological opti- mization can be effectively utilized to automatically design photonic devices where classical device architectures and structures designed by humans have poor performance. This work also proposes an initialization procedure for generating initial parameters for the optimization procedure. The structure optimized in this work was seeded using the initialization procedure showcasing its validity and effectiveness.
Emerging Contaminants in Groundwater and Surface Water at a Mine Reclamation Site: Occurrence, Fate and Remediation
(University of Waterloo, 2026-07-09) Yuan, Yizhi
Mine operations can generate large volumes of sulfide-rich waste rock and tailings. When exposed to atmospheric O2 and water, sulfide minerals can oxidize, producing low-quality drainage that contains high concentrations of dissolved metal(loid)s, sulfate, and acid. To limit the release of these toxic substances and promote landscape revegetation, municipal biosolids are increasingly utilized in mine rehabilitation programs. A multilayer cover system, consisting of a 0.5 m biosolids amended organic carbon (OC) layer and a 2 m desulfurized tailings (DST) layer, was applied on the high-sulfide tailings area in northern Ontario to retain moisture in the underlying tailings at high degrees of saturation, and promote revegetation of the landscape. Water samples from the vadose and saturated zones in the covered tailings system were collected versus depth using discrete sampling, whereas adjacent surface water was monitored using both discrete sampling and two passive samplers (diffusive gradients in thin films (DGT) and polar organic chemical integrative samplers (POCIS)) to assess spatial and temporal variations in major ions, trace elements, pharmaceutical and personal care products (PPCPs), artificial sweeteners, and per- and polyfluoroalkyl substances (PFASs) over a two-year period. Field investigations showed improved geochemical conditions below the cover system. In the vadose zone, the composite cover maintained circumneutral porewater pH through O2 consumption by OC, the enhanced neutralization capacity provided by added CaO, and the restriction of O2 infiltration in the high-moisture content DST layer, which effectively limited sulfide mineral oxidation compared to the acidic conditions (pH 3–4) observed in uncovered areas. While elevated concentrations of SO₄²⁻ and trace metals (e.g., Ni, Co, Mn, Cu, Zn) were observed in the subsurface groundwater due to historical oxidation, lower Fe concentrations beneath the biosolids layer are attributed to precipitation of goethite favoured under the circumneutral pH conditions. Concentrations of major ions and trace elements peaked adjacent to the tailings area (Ca: 152–298 mg L-1; SO42-: 347–745 mg L-1, Fe: 122–715 µg L-1; Ni: 810–1960 µg L-1) then decreased downstream within the alkaline treatment system decreasing critical trace element concentrations to well below regulatory limits (e.g., 6.0–426 µg L⁻¹ for Fe; 15.5–663 µg L⁻¹ for Ni). Porewater and groundwater monitoring indicated leaching of five pharmaceutical and personal care products (PPCPs) (95% within 480 hours), which followed a double first-order in parallel (DFOP) kinetic mechanism. The defluorination process approached 44.7±0.5% at 40 minutes and was accompanied by the formation of various shorter-chained PFASs and possible generation of organic acids (e.g., formic and acetic acid), indicating concurrent decarboxylation and defluorination pathways. Fluoride recovery, as the sum of the total inorganic and organic fluorine, reached a maximum of 67.4±1.5% at 40 min and decreased to 37.6±1.1% at 240 h. Given the near-complete removal of both PFOA and PFOS and low masses of generated short-chained PFASs (C4-C6), it is likely that PFOA and PFOS were transformed into PFBA, PFPeS and/or ultrashort-chain PFASs (C<4) that were not analyzed in the study. Alternatively, geochemical analysis indicated a potential fluoride sink via precipitation of fluorapatite associated with Ca and phosphate release from biochar. These outcomes demonstrate the feasibility of nZnNi-BC as an effective material for PFAS degradation and highlights the importance of geochemical sinks in controlling fluoride mass balance.