Scenario analysis of energy consumption and related emissions in the transportation industry-a case study of Shaanxi Province.

In the context of pursuing carbon neutrality and balancing the use of fossil fuels with renewable energy, the transportation industry faces the challenge of accurately predicting energy demand, related emissions, and assessing the effectiveness of energy technologies and policies. This is crucial for formulating energy management plans and reducing carbon dioxide (CO2) and atmospheric pollutant emissions. Currently, research on energy consumption and emission forecasting primarily relies on energy consumption quantities and emission factors, which lack precision. This study employs the low emissions analysis platform (LEAP) model, utilizing a "bottom-up" modeling approach combined with scenario analysis to predict and analyze the energy demand and related emissions in the transportation industry. Compared to previous studies, the methodological framework proposed in this research offers higher precision and can explore energy-saving and emission-reduction pathways for different modes of transport, providing a valuable energy forecasting tool for transport policy formulation in other regions. The forecast results indicate that under the business-as-usual (BAU) scenario, by 2049, the energy consumption and related emissions in Shaanxi Province's transportation industry are expected to increase by 1.15 to 1.85 times compared to the baseline year. In the comprehensive (CP) scenario, the industry is projected to reach a carbon peak around 2033. The study also finds that energy consumption and emissions predominantly originate from private passenger vehicles, highway freight, and civil aviation passenger, which have the greatest potential for emission reduction under the transport structure optimized (TSO) scenario. Therefore, policymakers should consider regional development characteristics, combine different transportation modes, and specifically analyze the emission reduction potential of the transportation industry in various regions, formulating corresponding reduction policies accordingly.

Analysis of the carbon emission driving factors and prediction of a carbon peak scenario--A case study of Xi'an city.

The continuous growth of global carbon emissions has become the focus of attention in political and academic circles in various countries. Understanding the driving factors of change in urban carbon emissions and predicting the peak of carbon emissions is of great significance for guiding the formulation of urban as well as national carbon emission reduction policies. Using Xi'an as an example, this study analyses the changing trend of its carbon emissions over the past 20 years. Based on carbon emissions and total economic volume, a Tapio decoupling elasticity analysis model was constructed, the decoupling coefficient of Xi'an from 2000 to 2020 was calculated, and the decoupling status of economic growth and carbon emissions were analysed. Using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition to analyse the driving factors of the city's carbon emissions, combined with a multi-scenario forecasting method, three different scenarios were subdivided, and the approximate time of Xi'an's carbon peak was estimated. The results show that from 2000 to 2020, the overall carbon emissions in Xi'an showed an upwards trend. In recent years, the decoupling status of economic growth and carbon emissions in Xi'an has been ideal, and the effect of carbon emission reduction is obvious. Population and per capita gross domestic product (GDP) have a positive driving effect on carbon emissions, and energy intensity has a negative driving force on carbon emissions. During early years, the carbon intensity of energy consumption showed a positive effect on carbon emissions. With the improvement of the energy structure, the intensity of energy consumption inhibits the growth of carbon emissions. Under the three scenarios of low carbon, baseline and high carbon, the carbon peak years will be achieved approximately in 2016, 2025 and 2035, and the corresponding carbon peaks are approximately 29.5 million tons, 29.66 million tons and 31 million tons, respectively.

Effect of permanganate oxidation on the photoreactivity of dissolved organic matter for photodegradation of typical pharmaceuticals.

Permanganate has been widely used in the remediation of contaminated water due to its relatively strong oxidation properties and ease of use. The ubiquitous dissolved organic matter (DOM) in natural waters causes a significant sink of permanganate in treatments, which further impacts the photoformation of reactive species and the removal of trace pollutants by DOM. Significantly, the effect of permanganate oxidation on the photoreactivity of DOM remains unknown. The present paper investigated for the first time the photophysical and photochemical properties variation of DOM from different sources after permanganate oxidation. Results showed that the permanganate oxidation caused a decrease in UV absorbance, fluorescence intensity, aromaticity, and molecular weight for all tested DOM samples, as well as photoformation rate of DOM triplet states (3DOM⁎), singlet oxygen (1O2), and hydroxyl radical (OH) under simulated sunlight. Quantum yield of 1O2 showed positively linear correlations with both triplet quantum yield coefficient (fTMP) and E2/E3 (ratio of absorbance at 254 and 365 nm) for all the DOM samples before and after permanganate oxidation. The quantum yield of OH exhibited no significant correlation with fTMP or E2/E3. Permanganate oxidation inhibited the DOM-photosensitized indirect photodegradation of pollutants that do not absorb sunlight (e.g., decreased by 15-29%). For the tested pollutants that undergo direct photolysis under sunlight, their photodegradation was promoted (e.g., increased by 1-19%) in the permanganate oxidized DOM solutions due to the decrease of light-screening effect by DOM. These findings suggest that permanganate oxidation affects the photoreactivity of DOM and the corresponding photochemical fate of organic pollutants in natural waters.

Photogeneration of Reactive Species from Biochar-Derived Dissolved Black Carbon for the Degradation of Amine and Phenolic Pollutants.

Due to agricultural waste combustion and large-scale biochar application, biochar-derived dissolved black carbon (DBC) is largely released into surface waters. The photogeneration of reactive species (RS) from DBC plays an important role in organic pollutant degradation. However, the mechanistic interactions between RS and pollutants are poorly understood. Here, we investigated the formation of DBC triplet states (3DBC*), singlet oxygen (1O2), and hydroxyl radical (•OH) in straw biochar-derived DBC solutions and photodegradation of typical pharmaceuticals and personal care products (PPCPs). Laser flash photolysis and electron spin resonance spectrometry showed that DBC exhibited higher RS quantum yields than some well-studied dissolved organic matter. The RS caused rapid degradation of atenolol, diphenhydramine, and propylparaben, selected as target PPCPs in this study. The 3DBC* contributed primarily to the oxidation of selected PPCPs via one-electron-transfer interaction, with average reaction rate constants of 1.15 × 109, 1.41 × 109, and 0.51 × 109 M-1 s-1, respectively. •OH also participated in the degradation and accounted for approximately 2.7, 2.5, and 18.0% of the total removal of atenolol, diphenhydramine, and propylparaben, respectively. Moreover, the photodegradation products were identified using high-resolution mass spectrometry, which further confirmed the electron transfer and •OH oxidation mechanisms. These findings suggest that DBC from the combustion process of agricultural biomass can efficiently induce the photodegradation of organic pollutants under sunlight in aquatic environments.

Effect of UV254 disinfection on the photoformation of reactive species from effluent organic matter of wastewater treatment plant.

UV254 is one of the main disinfection methods used in wastewater treatment plants (WWTPs) for the inactivation of pathogens in the effluents before being discharged into the receiving waters. The effluent organic matters (EfOM) are well-known photosensitizers for the generation of reactive species, mainly including the triplet states of EfOM (3EfOM*), singlet oxygen (1O2) and hydroxyl radical (•OH), which contribute to the removal of trace pollutants in water. However, the effect of UV254 disinfection on the photoreactivity of EfOM remains unclear. Here we investigated the photophysical and photochemical properties variation of EfOM after UV254 disinfection, along with humic substances (HS) as comparison. The UV254 disinfection caused a decrease of aromaticity, fluorescence intensity and molecular weight for all samples, while a reduction formation of triplet state of these dissolved organic matters (3DOM*), 1O2, hydrogen peroxide (H2O2), and superoxide anions (O2•-) under simulated sunlight was observed. In contrast, the generation of •OH was increased after UV254 disinfection. The quantum yield of 1O2 was positively correlated with triplet quantum yield coefficient (fTMP) in all cases. However, the quantum yield of •OH exhibited positive and negative correlations with fTMP for EfOM and HS, respectively. The quantum yields showed positive correlations with E2/E3 (ratio of the absorbance at 254 to 365 nm) for untreated DOM samples, while for the first time we found the trends differ distinctly after UV254 disinfection. These findings indicate that UV254 disinfection in WWTPs significantly increases the potential of •OH photoproduction from effluents and the cost-effective solar irradiation after UV254 disinfection is expected to be a novel technique for further removal of pathogen and trace organic pollutants in wastewater effluents and receiving waters.