Green finance and high-pollution corporate compensation - Empirical evidence from green credit guidelines.

With the increasing focus on Environmental, Social, and Governance (ESG) and Corporate Social Responsibility (CSR) on a global scale, stakeholders expect businesses to transform and enhance social responsibility. Over time, ESG and CSR have developed into vital performance metrics for businesses. Businesses are actively putting improvement measures into place in response to this new paradigm in order to stay competitive in this changing environment. China's dual commitment to CSR and sustainable development is in line with wider objectives, such as resolving issues of pay inequality. In 2012, the China Banking Regulatory Commission (CBRC) unveiled the "Green Credit Guidelines" (GCG), which take corporate governance's environmental considerations into account. These regulations set standards and specifically target high-pollution corporations. Companies may need to restructure their corporate structures and create efficient governance mechanisms in order to comply with these regulations and reduce carbon emissions. This will have an impact on the compensation packages of executives and regular employees. The most important question is how the "GCG" will affect the wage disparity in highly polluting companies. This study examines the 2012 "GCG" and its potential to reduce internal wage disparities, viewing it as a critical element of green financial policy. The paper uses data from Chinese A-share listed companies from 2007 to 2020. Besides, it uses the Difference-in-Differences method to assess the impact of China's GCG, treating its implementation as a quasi-natural experiment and controlling for concurrent policy effects to precisely identify its net impact on corporate carbon emissions and internal wage disparities. The findings show that "GCG" considerably closed internal wage disparities. Furthermore, the "GCG" has a path of guidance, incentives, and punishments that reduce internal wage disparities and promote a more equitable wage distribution within businesses. According to heterogeneity analysis, policies have a greater impact on the wage gap in businesses that are highly dependent on outside funding and have political connection. In order to achieve a compensation balance and meet the objectives of social responsibility and corporate sustainable development, the government should strengthen the complementary effects of green financial policies. The compensation balance in highly polluting companies has important theoretical and practical ramifications. On the one hand, it represents the convergence of income equality, corporate governance, and environmental responsibility. It helps to expand knowledge of sustainable development, fair compensation, and environmental policies. On the other hand, the widening pay disparity between executives and average employees reflects the exacerbation of income inequality in China, which could potentially impact companies' long-term development. Conversely, a well-balanced pay plan can improve worker productivity and motivation while empowering stakeholders to make wise investment choices.

Incorporation of Epoxy Carbon onto CeO2-Supported Pt to Tackle the CO Self-Poisoning Issue.

The catalytic oxidation of carbon monoxide (CO) under ambient conditions plays a crucial role in the abatement of indoor CO, which poses risks to human health. Despite the notable activity exhibited by Pt-based catalysts in CO oxidation, their efficacy is usually diminished by the CO self-poisoning issue. In this work, three different Pt/CeO2-based catalysts, which have distinct coordinative environments of Pt but an identical Pt/CeO2 substrate structure, were synthesized by activating the catalyst with CO using different temperatures and durations. Compared with clean and graphite-covered Pt on CeO2, the one modified by epoxy carbon showed higher activity and stability. The combination of characterizations and density functional theory modeling demonstrated that the clean Pt on CeO2 rapidly deactivated due to the CO self-poisoning albeit high initial activity, and conversely, low initial activity was observed for the more stable graphite-covered catalyst due to the obstruction of the Pt site. In contrast, epoxy carbon species on Pt shifted the d-band of Pt to lower energy, weakening the Pt-CO binding strength. Such a modification mitigated the self-poisoning effect while maintaining ample active sites and enabling the complete oxidative removal of CO under ambient conditions. This work may provide a general approach to tackling the self-poisoning issue.

Enhancing oxidation reaction over Pt-MnO2 catalyst by activation of surface oxygen.

Formaldehyde (HCHO) and carbon monoxide (CO) are both common air pollutants and hazardous to human body. It is imperative to develop the catalyst that is able to efficiently remove these pollutants. In this work, we activated Pt-MnO2 under different conditions for highly active oxidation of HCHO and CO, and the catalyst activated under CO displayed superior performance. A suite of complementary characterizations revealed that the catalyst activated with CO created the highly dispersed Pt nanoparticles to maintain a more positively charged state of Pt, which appropriately weakens the Mn-O bonding strength in the adjacent region of Pt for efficient supply of active oxygen during the reaction. Compared with other catalysts activated under different conditions, the CO-activated Pt-MnO2 displays much higher activity for oxidation of HCHO and CO. This research contributes to elucidating the mechanism for regulating the oxidation activity of Pt-based catalyst.

Electronic Modification by Transitional Metal Dopants to Tune the Oxidation Activity of Pt-CeO2-Based Catalysts.

While utilization of transitional metals as a promoter has been extensively studied to enhance the activity of Pt-based catalysts for the oxidation of formaldehyde (HCHO), there is still a lack of well elucidated property-function relationship for the rational selection of a promoter in catalyst design. Herein, we modified a Pt/CeO2 catalyst with two transitional metal dopants (i.e., Mn and Cu) that showed negligible influence on the physical structure of the Pt-CeO2 matrix but distinct effects on the activity of the catalyst. Complementary characterizations combined with density functional theory modeling revealed that the transitional metal dopants significantly modified the electronic structure of the catalyst and shifted the d-band of Pt to higher energy with different extents, which may tune the bonding strength of HCHO/intermediates with the Pt-CeO2 interface domain. The catalyst with moderate bonding strength (i.e., Pt-Mn/CeO2) displayed the highest reactivity under the ambient condition, while Pt-Cu/CeO2 with the highest bonding strength showed a dramatically decreased activity. No correlation was observed between the abundancy of the active oxygen and catalytic activity, likely due to the oxygen supply having a much higher rate than the rate-determining step. This work contributes to the elucidation about the property-function relationship of a transitional metal dopant in Pt-based catalysts for the oxidation of HCHO.

Correction: Tunable deep-blue luminescence from ball-milled chlorine-rich Csx(NH4)1-xPbCl2Br nanocrystals by ammonium modulation.

Correction for 'Tunable deep-blue luminescence from ball-milled chlorine-rich Csx(NH4)1-xPbCl2Br nanocrystals by ammonium modulation' by Hongfei Xiao et al., Chem. Commun., 2022, 58, 3827-3830, DOI: 10.1039/D1CC07125D.

Tunable deep-blue luminescence from ball-milled chlorine-rich Csx(NH4)1-xPbCl2Br nanocrystals by ammonium modulation.

For the first time, a novel class of deep-blue (DB)-emitting Csx(NH4)1-xPbCl2Br (0.3 ≤ x ≤ 1) perovskite nanocrystals (PNCs) were prepared by a facile ligand-assisted one-step ball milling method. The resulted PNCs are characterized by high chlorine content (66.7%) and excellent color purity. Their photoluminescence position can be finely modulated from 434 nm to 447 nm, which extends notably beyond the current Rec. 2020 color standard, by the NH4+ content. Among them, Cs0.3(NH4)0.7PbCl2Br shows the highest quantum yield close to 40%. The PNCs exhibit high phase and optical stability under ambient conditions and UV light according to the NH4+ content. This work offers a new avenue to produce DB perovskites for future full-color displays and optoelectronics.

An improved PD-AsLS method for baseline estimation in EDXRF analysis.

Baseline correction is an important step in energy-dispersive X-ray fluorescence analysis. The asymmetric least squares method (AsLS), adaptive iteratively reweighted penalized least squares method (airPLS), and asymmetrically reweighted penalized least squares method (arPLS) are widely used to automatically select the data points for the baseline. Considering the parametric sensitivity of the aforementioned methods and the statistical characteristics of the X-ray energy spectrum, this paper proposes an asymmetrically reweighted penalized least squares method based on the Poisson distribution (PD-AsLS) to automatically correct the baseline of X-ray spectra. Monte Carlo (MC) simulation is used to obtain the background spectrum, and PD-AsLS is used to estimate the baseline of the background. The relative error and the absolute error between the simulated background and PD-AsLS estimated background are used to determine the accuracy of PD-AsLS. The correlation coefficient (COR) and the root mean square error (RMSE) between the estmated baseline and the real baseline are calculated, and results of PD-AsLS are compared with results of three other classical methods (arPLS, airPLS and AsLS) to evaluate the reliability of PD-AsLS. The results of PD-AsLS show that the COR is above 0.95 and RMSE is less than 6. The stability and the practicability of PD-AsLS are also evaluated in experiments. A sample is measured five time to get its X-ray energy spectra, and the coefficient of variation (CV) of the estimated baseline is smaller than that of measured spectra. Experiments show that PD-AsLS can estimate baselines better than arPLS without any overestimation. Those results indicate that PD-AsLS can reliably estimate the baselines of X-ray spectra and effectively suppress the statistical fluctuation.

Layer-Wise Floorplan Extraction for Automatic Urban Building Reconstruction.

Urban building reconstruction is an important step for urban digitization and realisticvisualization. In this paper, we propose a novel automatic method to recover urban building geometry from 3D point clouds. The proposed method is suitable for buildings composed of planar polygons and aligned with the gravity direction, which are quite common in the city. Our key observation is that the building shapes are usually piecewise constant along the gravity direction and determined by several dominant shapes. Based on this observation, we formulate building reconstruction as an energy minimization problem under the Markov Random Field (MRF) framework. Specifically, point clouds are first cutinto a sequence of slices along the gravity direction. Then, floorplans are reconstructed by extracting boundaries of these slices, among which dominant floorplans are extracted and propagated to other floors via MRF. To guarantee correct propagation, a new distance measurement for floorplans is designed, which first encodes floorplans into strings and then calculates distances between their corresponding strings. Additionally, an image based editing method is also proposed to recover detailed window structures. Experimental results on both synthetic and real data sets have validated the effectiveness of our method.