Global warming is shifting the relationships between fire weather and realized fire-induced CO2 emissions in Europe

Backbone Engineering of Polymeric Catalysts for High-Performance CO2 Reduction in Bipolar Membrane Zero-Gap Electrolyzer

Bipolar membranes (BPMs) have emerged as a promising solution for mitigating CO2 losses, salt precipitation and high maintenance costs associated with the commonly used anion-exchange membrane electrode assembly for CO2 reduction reaction (CO2RR). However, the industrial implementation of BPM-based zero-gap electrolyzer is hampered by the poor CO2RR performance, largely attributed to the local acidic environment. Here, we report a backbone engineering strategy to improve the CO2RR performance of molecular catalysts in BPM-based zero-gap electrolyzers by covalently grafting cobalt tetraaminophthalocyanine onto a positively charged polyfluorene backbone (PF-CoTAPc). PF-CoTAPc shows a high acid tolerance in BPM electrode assembly (BPMEA), achieving a high FE of 82.6 % for CO at 100 mA/cm2 and a high CO2 utilization efficiency of 87.8 %. Notably, the CO2RR selectivity, carbon utilization efficiency and long-term stability of PF-CoTAPc in BPMEA outperform reported BPM systems. We attribute the enhancement to the stable cationic shield in the double layer and suppression of proton migration, ultimately inhibiting the undesired hydrogen evolution and improving the CO2RR selectivity. Techno-economic analysis shows the least energy consumption (957 kJ/mol) for the PF-CoTAPc catalyst in BPMEA. Our findings provide a viable strategy for designing efficient CO2RR catalysts in acidic environments.

Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review

The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.

Breakthrough applications of porous organic materials for membrane-based CO2 separation: a review

Over the last decades, porous organic materials (POMs) have been extensively employed in various industrial approaches including gas separation, catalysis and energy production due to possessing indisputable advantages like great surface area, high permeability, controllable pore size, appropriate functionalization and excellent processability compared to traditional substances like zeolites, Alumina and polymers. This review presents the recent breakthroughs in the multifunctional POMs for potential use in the membrane-based CO2 separation. Some examples of highly-selective membranes using multifunctional POMs are described. Moreover, various classifications of POMs following with their advantages and disadvantages in CO2 separation processes are explained. Apart from reviewing the state-of-the-art POMs in CO2 separation, the challenges/limitations of POMs with tailored structures for reasonable application are discussed.

Genome-Wide Identification, Characterization, and Expression Analysis of the BES1 Family Genes under Abiotic Stresses in Phoebe bournei

The BRI1 EMS suppressor 1(BES1) transcription factor is a crucial regulator in the signaling pathway of Brassinosteroid (BR) and plays an important role in plant growth and response to abiotic stress. Although the identification and functional validation of BES1 genes have been extensively explored in various plant species, the understanding of their role in woody plants-particularly the endangered species Phoebe bournei (Hemsl.) Yang-remains limited. In this study, we identified nine members of the BES1 gene family in the genome of P. bournei; these nine members were unevenly distributed across four chromosomes. In our further evolutionary analysis of PbBES1, we discovered that PbBES1 can be divided into three subfamilies (Class I, Class II, and Class IV) based on the evolutionary tree constructed with Arabidopsis thaliana, Oryza sativa, and Solanum lycopersicum. Each subfamily contains 2-5 PbBES1 genes. There were nine pairs of homologous BES1 genes in the synteny analysis of PbBES1 and AtBES1. Three segmental replication events and one pair of tandem duplication events were present among the PbBES1 family members. Additionally, we conducted promoter cis-acting element analysis and discovered that PbBES1 contains binding sites for plant growth and development, cell cycle regulation, and response to abiotic stress. PbBES1.2 is highly expressed in root bark, stem bark, root xylem, and stem xylem. PbBES1.3 was expressed in five tissues. Moreover, we examined the expression profiles of five representative PbBES1 genes under heat and drought stress. These experiments preliminarily verified their responsiveness and functional roles in mediating responses to abiotic stress. This study provides important clues to elucidate the functional characteristics of the BES1 gene family, and at the same time provides new insights and valuable information for the regulation of resistance in P. bournei.

Establishing the relationship between wildfire smoke and performance metrics on finished beef cattle in Western Rangelands

Identifying causal relationships is complicated. Researchers usually overlook causality behind relationships which can generate misleading associations. Herein, we carefully examine the parametric relationship and causality between wildfire smoke exposure and animal performance and behavior metrics over a period of 2 yr in Reno, Nevada. The animals in the 2020 smoke season were grain-finished (n = 12) and grass-finished (n = 12), whereas the animals during the 2021 season were fed under the same diet but finished with either a hormonal implant (n = 9), or without (n = 9). The dataset included daily records of feed intake (FI), body weight (BW), water intake (WI), average daily gain (ADG), and WI behavior (time spent drinking [TSD]; water intake events [WIE]; no-WIE [NWIE]). Variable tree length Bayesian additive regression trees (BART) were utilized to investigate the relationships between air quality index (AQI), particulate matter 2.5 μm (PM2.5) and 10 μm (PM10), NO2, SO2, Ozone, and CO levels in the air (sensors < 1.6 km from animals) with the animal data. Additionally, linear mixed models with a 7-d lag were used to evaluate parametric relationships among the same variables. All statistical analyses were performed on R Statistical Software (R Core Team 2023). Under the linear mixed model with a 7-d lag, significant positive and negative associations were found for all parameters examined (P < 0.05). Negative associations were found between FI, WI, ADG, BW, WIE, NWIE, TSD, and PM2.5 (P < 0.05) for at least one animal group. Positive linear associations between wildfire smoke parameters and the metrics evaluated were more variable and dependent on year, treatment, and smoke parameters. When examining the credible intervals and the variable importance in the BART, relationships were more difficult to identify. However, some associations were found for Ozone, AQI, NO2, CO, and PM10 (P < 0.05). Overall, our results carefully examine the relationship between smoke parameters and cattle performance and present interesting pathways previously unexplored that could guide early culling/finishing of animals to avoid economic losses associated with performance decrease in response to wildfire smoke exposure. Though interesting associations are found under linear mixed models, causality is difficult to establish, which highlights the need for controlled exposure experiments.

Extreme fire weather in Chile driven by climate change and El Niño-Southern Oscillation (ENSO)

A string of fierce fires broke out in Chile in the austral summer 2023, just six years after the record-breaking 2017 fire season. Favored by extreme weather conditions, fire activity has dramatically risen in recent years in this Andean country. A total of 1.7 million ha. burned during the last decade, tripling figures of the prior decade. Six of the seven most destructive fire seasons on record occurred since 2014. Here, we analyze the progression during the last two decades of the weather conditions associated with increased fire risk in Central Chile (30°-39° S). Fire weather conditions (including high temperatures, low humidity, dryness, and strong winds) increase the potential for wildfires, once ignited, to rapidly spread. We show that the concurrence of El Niño and climate-fueled droughts and heatwaves boost the local fire risk and have decisively contributed to the intense fire activity recently seen in Central Chile. Our results also suggest that the tropical eastern Pacific Ocean variability modulates the seasonal fire weather in the country, driving in turn the interannual fire activity. The signature of the warm anomalies in the Niño 1 + 2 region (0°-10° S, 90° W-80° W) is apparent on the burned area records seen in Central Chile in 2017 and 2023.

Mapping opportunities for the use of land management strategies to address fire risk in Europe

Many parts of Europe face increasing challenges managing wildfires. Although wildfire is an integral part of certain ecosystems, fires in many places are becoming larger and more intense, driven largely by climate change, land abandonment, and changes in fuel management with important socioeconomic, environmental, and ecosystem services consequences for Europe. In order to envision a comprehensive fire risk mitigation strategy for Europe, a spatial assessment of opportunities to manage fuels at the landscape-scale is needed. Our study explored the suitability of three land management strategies (LMS)-herbivory, mechanical fuel removal, and prescribed burn-which can create more heterogenous fuelscapes, thereby reducing an element of fire risk. We created suitability maps for each of the LMS using adoption factors identified in a systematic literature review (n = 123). We compared these maps with areas of historical fire occurrence as a proxy for fire risk to prioritize key areas for intervention. We found that over a quarter of Europe was suitable for multiple LMS within areas of greater fire risk, creating opportunities for concurrent and synergistic use of the strategies. Options were more limited in areas of southern Europe, where prescribed burn was found to be uniquely viable amongst the LMS evaluated. Opportunities were also restricted in some areas of high fire risk in northern Europe, where herbivory was found to be the only suitable LMS. Our findings take a wide-view of fuel management to target landscape-scale decision making focused on reducing fire risk. However, many other factors must be taken into account to successfully manage fuels at local scales, including the socio-cultural appropriateness of the LMS, the viability of incentive schemes, and possible trade-offs with other management goals, such as carbon storage and biodiversity.

Unlocking full and fast conversion in photocatalytic carbon dioxide reduction for applications in radio-carbonylation

Harvesting sunlight to drive carbon dioxide (CO₂) valorisation represents an ideal concept to support a sustainable and carbon-neutral economy. While the photochemical reduction of CO₂ to carbon monoxide (CO) has emerged as a hot research topic, the full CO₂-to-CO conversion remains an often-overlooked criterion that prevents a productive and direct valorisation of CO into high-value-added chemicals. Herein, we report a photocatalytic process that unlocks full and fast CO₂-to-CO conversion (<10 min) and its straightforward valorisation into human health related field of radiochemistry with carbon isotopes. Guided by reaction-model-based kinetic simulations to rationalize reaction optimisations, this manifold opens new opportunities for the direct access to ¹¹C- and ¹⁴C-labeled pharmaceuticals from their primary isotopic sources [¹¹C]CO₂ and [¹⁴C]CO₂.

The relationship between knowledge and disaster preparedness of undergraduates responding to forest fires

Forest and land fires are disasters that regularly occur on the island of Kalimantan, Indonesia. Higher education students on the island of Kalimantan are considered vulnerable to these disasters, hence the need for mandatory disaster knowledge and preparedness for every individual in the area. This research aimed to: (1) determine disaster knowledge and student preparedness in dealing with forest and land fire disasters, (2) determine the relationship between knowledge and student preparedness. This study used a quantitative correlation method with a questionnaire. The data were processed using the Statistical Package for the Social Sciences 21. The research sample used purposive sampling because it followed the needs of the study, which involved 300 students affected by forest fires, representing three universities located in a forest fire-prone area in West Kalimantan province, Indonesia. Each campus has 100 students, a total of 300 students. The results showed as many as 284 students had experienced forest and land fire disasters. In addition, 202 out of 284 students were known to have low disaster knowledge. Four main parameters of disaster preparedness were used to measure student preparedness, namely (1) knowledge and attitudes, (2) emergency response plans, (3) disaster warning system and (4) resource mobilisation. The number of students with high preparedness was 141, while 143 had low preparedness. Thus, student preparedness measures need to be increased to avoid disaster impact.

CONTRIBUTION

Based on the data analysis, students' knowledge and preparedness to face forest fires are positively related. It was shown that the higher the learning of students, the higher their readiness and vice versa. It is suggested that there is a need for increasing knowledge and preparedness actions for students in dealing with forest fire disasters through regular disaster lectures, simulations and training so that they can make the right decisions in coping with disasters.

Conversion of Carbon Dioxide into Chemical Vapor Deposited Graphene with Controllable Number of Layers via Hydrogen Plasma Pre-Treatment

In this work, we report the conversion of carbon dioxide (CO₂) gas into graphene on copper foil by using a thermal chemical vapor deposition (CVD) method assisted by hydrogen (H₂) plasma pre-treatment. The synthesized graphene has been characterized by Raman spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy. The results show the controllable number of layers (two to six layers) of high-quality graphene by adjusting H₂ plasma pre-treatment powers (100-400 W). The number of layers is reduced with increasing H₂ plasma pre-treatment powers due to the direct modification of metal catalyst surfaces. Bilayer graphene can be well grown with H₂ plasma pre-treatment powers of 400 W while few-layer graphene has been successfully formed under H₂ plasma pre-treatment powers ranging from 100 to 300 W. The formation mechanism is highlighted.