Changes In Emissions Research Articles

Triple Pillar for Sustainability of Accounting Evaluation of Carbon Emissions and Climate Change

This study is among the first to address the relationship between accounting and adaptation to climate change. Aramco is a well-known company in the Middle East that produces oil, and it was used as a case study. This study examines the theoretical underpinnings of accounting assessment of carbon emissions arising from climate change and their influence on sustainability. The questionnaire was distributed to approximately 150 Saudi Arabian managers. The researcher used an analytical descriptive technique and the Statistical Packages Program for Social Sciences (SPSS) to assess the sample, fill out, tabulate, analyze the data, and test the hypotheses. The findings demonstrate that accounting for carbon emissions affects sustainable development in its three pillars-economic, social, and environmental. Further, the sub-hypothesis’s results indicate that accounting for carbon emissions statistically impacts sustainable development’s economic and environmental aspects. Accounting for carbon emissions has no discernible impact on sustainable development through the social component. The researcher advocated that the social aspect of sustainable development should be given attention. Large corporations are made aware of their significance in achieving environmental sustainability and that failing to adopt labor and human rights standards will result in companies being held accountable.

Dynamic Simulation of Carbon Emission Peak in City-Scale Building Sector: A Life-Cycle Approach Based on LEAP-SD Model

Systematically predicting carbon emissions in the building sector is crucial for formulating effective policies and plans. However, the timing and potential peak emissions from urban buildings remain unclear. This research integrates socio-economic, urban planning, building technology, and energy consumption factors to develop a LEAP-SD model using Shenzhen as a case study. The model considers the interrelationship between socio-economic development and energy consumption, providing more realistic scenario simulations to predict changes in carbon emissions within the urban building sector. The study investigates potential emission peaks and peak times of buildings under different population and building area development scenarios. The results indicate that achieving carbon peaking by 2030 is challenging under a business as usual (BAU) scenario. However, a 10% greater reduction in energy intensity compared to BAU could result in peaking around 2030. The simulation analysis highlights the significant impact of factors such as population growth rate, per capita residential building area, and energy consumption per unit building area and the need for a comprehensive analysis. It provides more realistic scenario simulations that not only enhance theories and models for predicting carbon emissions but also offer valuable insights for policymakers in establishing effective reduction targets and strategies.

Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Sensing the Small Change of Intermolecular Distance in Supramolecular Assembly by Using the Tunable Emission Wavelength of AIE-Active Luminogens.

The distinct molecular states - single molecule, assembly, and aggregate - of two ionic macromolecules, TPPE-APOSS and TPE-APOSS, are easily distinguishable through their tunable fluorescence emission wavelengths, which reflect variations in intermolecular distances. Both ionic macromolecules contain aggregation-induced emission (AIE) active moieties whose emission wavelengths are directly correlated to their mutual distances in solution: far away from each other as individual molecules, maintaining a tunable and relatively long distance in electrostatic interactions-controlled blackberry-type assemblies (microphase separation), or approaching van der Waals close distance in aggregates (macrophase separation). Furthermore, within the blackberry assemblies, the emission wavelength decreases monotonically with increasing assembly size, indicative of shorter intermolecular distances at nanoscale. The emission changes of TPPE-APOSS blackberry assemblies can even be visually distinguishable by eyes when their sizes and intermolecular distances are tuned. Molecular dynamics simulations further revealed that macromolecules are confined in various conformations by controllable intermolecular distances within the blackberry structure, thereby resulting in fluorescence emission with tunable wavelength.

Integrating Process Simulation and Life Cycle Assessment for Enhanced Process Efficiency and Reduced Environmental Impact in Ferromanganese Production

Process simulation was integrated with life cycle assessment to evaluate process efficiency and environmental impact of the production of manganese ferroalloys for various production modes and different ore mineralogies. Utilizing HSC Sim, the model was designed to evaluate the production process with or without a pretreatment step, where results for simulated cases using a four-zone ferromanganese furnace model were exported to openLCA for a complete life cycle assessment. Two main production scenarios were simulated: a closed ferromanganese furnace running on the duplex method and an open furnace running on the discard slag approach. The closed furnace scenario achieved a 17.5% reduction in energy consumption and a 16.2% decrease in direct CO2 emissions with CO-rich off-gas pretreatment. The open furnace scenario showed an 11.2% reduction in energy consumption with thermal solar energy pretreatment but no change in CO2 emissions.

An optimal global biochar application strategy based on matching biochar and soil properties to reduce global cropland greenhouse gas emissions: findings from a global meta-analysis and density functional theory calculation

Biochar has been extensively utilized to amend soil and mitigate greenhouse gas (GHG) emissions from croplands. However, the effectiveness of biochar application in reducing cropland GHG emissions remains uncertain due to variations in soil properties and environmental conditions across regions. In this study, the impact of biochar surface functional groups on soil GHG emissions was investigated using molecular model calculation. Machine learning (ML) technology was applied to predict the responses of soil GHG emissions and crop yields under different biochar feedstocks and application rates, aiming to determine the optimum biochar application strategies based on specific soil properties and environmental conditions on a global scale. The findings suggest that the functional groups play an essential role in determining biochar surface activity and the soil’s capacity for adsorbing GHGs. ML was an effective method in predicting the changes in soil GHG emissions and crop yield following biochar application. Moreover, poor-fertility soils exhibited greater changes in GHG emissions compared to fertile soil. Implementing an optimized global strategy for biochar application may result in a substantial reduction of 684.25 Tg year−1 CO2 equivalent (equivalent to 7.87% of global cropland GHG emissions) while simultaneously improving crop yields. This study improves our understanding of the interaction between biochar surface properties and soil GHG, confirming the potential of global biochar application strategies in mitigating cropland GHG emissions and addressing global climate degradation. Further research efforts are required to optimize such strategies.Graphical

Exploring resource-efficient urban mobility for sustainable low emission solutions: A case study of Ile-de-France, France.

Urban areas and their associated mobility stocks exert substantial environmental impacts, necessitating urgent mitigation efforts. However, prevailing research predominantly concentrates on operational requirements for urban mobility. Few stock studies have quantified the embodied environmental requirements of mobility stocks. This study quantified both the embodied and operational environmental requirements and examined the stock-flow-service indicators to offer a new perspective on options for low emissions on urban mobility. Focusing on the mobility dynamics of the Ile-de-France region and its three sub-regional zones from 2010 to 2018, our findings reveal a pronounced imbalance in the utilization of materials within different mobility modes (car, public transport, motorized two-wheelers, cycling, and pedestrian) across Paris, Petite Couronne, and Grande Couronne. Local disparities in the stock of mobility modes and their capacity to facilitate movement are evident, particularly when considering various service metrics (person-trip, person-travel time, and person-kilometer). Furthermore, the different patterns of service-flow-stock indicators among mobility modes are investigated to find their impacts on regional carbon emissions changes from 2010 to 2018. Stock turnover rate and service demand were the main drivers of embodied emissions of public transportation and cycling, while operational carbon intensity showed a major impact on car operational emissions. This study enriches our comprehension of the intricate interplay between resource utilization and the provision of people's mobility, thereby promoting sustainable mobility in the Ile-de-France region.

Naked eye detection of anions: Dihydrazone receptor-based visual sensing

In this study, we designed and synthesized a novel colorimetric sensor for fluoride ions by integrating a thienodicarbohydrazide framework with salicylaldehyde, resulting in a unique bis-hydrazone-phenol receptor. This sensor exhibited exceptional selectivity for fluoride and acetate ions in nonaqueous environments, with detection visible to the naked eye. Upon interaction with fluoride ions, the receptor underwent a significant red shift in its UV–Visible absorption spectrum, moving from an absorption maximum at 332 nm–380 nm, signalling the recognition event. Acetate ions induced a similar shift. The binding interactions were thoroughly investigated, with a Jobs plot revealing a 1:1 receptor-anion complex formation with fluoride ions and a 1:2 complex with acetate ions. Further validation came from 1H NMR titration, which confirmed the presence of hydrogen bonding interactions between the receptor and the ions. The receptor demonstrated remarkable binding constants of 5.2 × 10⁴ M−2 for acetate and 1.6 × 10⁴ M−1 for fluoride ions, highlighting its strong and selective affinity. Fluorescence titrations further confirmed the receptor's potential as a chemo sensor, showing distinct emission changes in the presence of fluoride and acetate ions. This study not only underscores the receptor's capability for visual detection of fluoride ions in non-aqueous systems but also paves the way for its application in diverse analytical and environmental settings.

Impact of methane and other precursor emission reductions on surface ozone in Europe: scenario analysis using the European Monitoring and Evaluation Programme (EMEP) Meteorological Synthesizing Centre – West (MSC-W) model

Abstract. The impacts of future methane (CH4) and other precursor emission changes are investigated for surface ozone (O3) in the United Nations Economic Commission for Europe (UNECE) region excluding North America and Israel (the EMEP region, for European Monitoring and Evaluation Programme) for the year 2050. The analysis includes a current legislation (CLE) and maximum feasible technical reduction (MFR) scenario, as well as a scenario that combines MFRs with an additional dietary shift that also meets the Paris Agreement objectives with respect to greenhouse gas emissions (LOW). For each scenario, background CH4 concentrations are calculated using a probabilistic Earth system model emulator and combined with other precursor emissions in a three-dimensional Eulerian chemistry-transport model. While focus is placed on peak season maximum daily 8 h average (MDA8) O3 concentrations, a range of other indicators for health and vegetation impacts are also discussed. Our analysis shows that roughly one-third of the total peak season MDA8 reduction achieved between the 2050 CLE and MFR scenarios is attributable to CH4 reductions, resulting predominantly from CH4 emission reductions outside of the EMEP region. The impact of other precursor emission reductions is split nearly evenly between the reductions inside and outside of the EMEP region. However, the relative importance of CH4 and other precursor emission reductions is shown to depend on the choice of O3 indicator, though indicators sensitive to peak O3 show generally consistent results. The analysis also highlights the synergistic impacts of CH4 mitigation as reducing solely CH4 achieves, beyond air quality improvement, nearly two-thirds of the total global warming reduction calculated for the LOW scenario compared to the CLE case.

Multiple Energy Transfer Modes From o‐Carborane Dyad Induced by Synergetic Conformational Regulations and Intense Circularly Polarized Luminescence in Self‐Assembly Aggregates

AbstractPhotothermal modulated excited conformations in traditional optoelectronic materials have been extensively investigated for the manipulation of emissive properties. However, photoinduced molecular synergetic conformational changes, which are promising for controlling intramolecular energy transfer modes through molecular orbital breaking, are never been explored. Herein, a novel o‐carborane dyad composed of carbazole units as electron donors and triazine derivatives as electron acceptors is demonstrated to achieve conformation‐dependent emissions and abundant emissions via synergetic conformational changes. Notably, the resulting dyad exhibited multiple conformational changes that induced emissions through different energy transfer modes involved “through space” and “through bond.” Exactly, the electron spin from singlet to triplet state took a flip accompanied by molecular orbitals from π–π molecular orbitals in the space charge transfer style to π and σ molecular orbitals in the bond charge transfer mode. The circularly polarized luminescence (CPL) properties are systematically investigated, exhibiting intense CPL with large glum values. These results provide novel perspectives for elucidating the complicated emission changes in aggregated states, as well as unique perspectives on the relationship between molecular conformations, energy transfer modes, and molecular orbital breaking.

Upconverting thermal history paint for investigations of short thermal events

The main goal of the work was to develop phosphorescent coating for investigations of surface temperature distribution resulted from short duration and high energy thermal events such as small rocket engine testing. For that purpose, we developed thermal history paint with upconverting Gd2O3: Er3+, Yb3+, Mg2+ nanopowder. The developed paint was heated by Joule effect with precise control over temperature and heating time. Photoluminescence signal of cooled samples was excited with 980 nm laser and collected in automatic manner with use of an optical fibre probe connected to photospectrometer. The results show that irreversible changes of paint emission are temperature and heating time specific for calcination temperatures from 700 °C to 1150 °C. Calibration curves were prepared for heating times of 10, 60 and 180 seconds. Finally, 2D surface temperature samples were determined with use of upconverting thermal history paint and compared to IR camera and pyrometric measurements. The results indicate that uncertainty of temperature measurement below 10 °C was achieved for temperatures above 1000 °C. It has been demonstrated that developed thermal history paint allows for measurements of 2D surface temperature distribution with high spatial resolution and good agreement to standard measurements techniques like thermal camera and pyrometer.

Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs)

Abstract. New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOM chemistry. Here, we incorporate a state-of-the-art biogenic HOM chemistry scheme with 96 chemical reactions to a global chemistry–climate model and quantify the contribution to global aerosols through HOM-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from −96 % to −15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that compared to turning off the organic nucleation rate, turning off organic initial growth results in a more substantial decrease in aerosol number concentrations. Globally, organics contribute around 45 % of the annual mean vertically integrated nucleation rate (at 1.7 nm) and 25 % of the vertically averaged growth rate. The inclusion of HOM-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the semi-explicit HOM mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make aerosol sensitive to changes in biogenic emissions.

Optimization of operational parameters of marine methanol dual-fuel engine based on based on RSM- MOPSO

Methanol and natural gas, as green fuels for environmental protection, have shown great potential in the field of maritime transportation. This study explores how the methanol energy fraction (MEF), exhaust gas recirculation (EGR), excess air ratio (λ), and engine injection timing (EIT) influence combustion and emission traits in marine dual-fuel (DF) engine. Initially, a DF engine model was formulated through experiments using CONVERGE software, while the CHEMKIN program devised a chemical mechanism involving 100 compounds and 512 reactions. The response surface methodology (RSM) was subsequently utilized to design the experiment and develop the regression model. The improved multi-objective particle swarm optimization (MOPSO) algorithm was applied to optimize three critical variables: brake thermal efficiency (BTE), carbon monoxide (CO), and nitrogen oxide (NOx) emissions. Ultimately, feature-optimized scenarios from the Pareto front were chosen for comparative evaluation to derive the optimal configuration. The results show that when the decision variables MEF, EGR, λ and EIT are 22.33 %, 10 %, 1.81 and 11°CA BTDC respectively, there is a better trade-off between the three target variables. Compared with the original case, the change of ITE, NOx and CO emissions in the optimal case are +0.97 %, −39.53 % and −14.51 %, respectively. Overall, based on the intelligent optimization approach, the rational selection of DF engine parameters improved the ITE and most NOx and CO emissions were effectively suppressed.

Monitoring small-scale bioreactor studies for media development using polarized total synchronous fluorescence spectroscopy (pTSFS) and synchronous light scattering (SyLS)

Biopharmaceutical process development often involves the use of small-scale bioreactors (SSBR) for optimizing media formulations and process conditions during scale up to commercial scale production. Two key process parameters (CPP) used in SSBR studies are protein titre and viable cell density (VCD). Here, we explore the efficacy of parallel polarized total synchronous fluorescence spectroscopy (TSFS||) and Synchronous Light Scattering (SyLS||) to qualitatively monitor these CPPs and quantitatively predict titre and VCD for a large-scale cell culture media optimization SSBR study. The study involved 71 different media formulations (50+ components each), and the bioprocess was run for 13 days or more. Samples were extracted at set times (Day 0, 3, 9, and 13) and clarified by centrifugation. TSFS|| spectra showed significant emission changes along with increased light scatter over the course of the bioprocess. SyLS|| measurements strongly correlated with particle size data obtained from Dynamic Light Scattering but did not correlate well with VCD probably because of the centrifugation-based sample preparation. Statistical and principal component analysis (PCA) of the pTSFS data showed that spectral variation was greater between media formulations than due to the evolving bioprocess. This prevented the development of accurate global prediction models for media performance (e.g., predicting product titre at day 9 from media spectra measured at day 0). However, classification methods were successfully used to select media subsets with better quantitative prediction accuracy based on spectral similarities. A practical binary (high/low performance) classification model based on Support Vector Machines was generated for media formulation screening. Combining emission and scatter measurements with multivariate data analysis provides a more holistic, multi-attribute bioprocess monitoring method that minimizes the need to use different offline analytical methods. This methodology can be used to monitor process trajectories and deviations, and ultimately be used to predict bioprocess CPPs when implemented on production scale processes where there is much less compositional variation in the media. We believe this SSBR-pTSFS/SyLS approach will provide a valuable resource to develop the design/parameter space for in-process monitoring at production scale from early-stage process/media development studies.

QSO MUSEUM. II. Search for extended Lyalpha emission around eight z~3 quasar pairs

Extended Lyalpha emission is routinely found around single quasars across cosmic time. However, few studies have investigated how such emission changes in fields with physically associated quasar pairs, which should reside in dense environments and are predicted to be linked through intergalactic filaments. We present VLT/MUSE snapshot observations (45 minutes/source) to unveil extended Lyalpha emission on scales of the circumgalactic medium (CGM) around the largest sample of physically associated quasar pairs to date, encompassing eight pairs (14 observed quasars) at $z 3$ with an $i$-band magnitude between 18 and 22.75, corresponding to absolute magnitudes $M_i(z=2)$ between -29.6 and -24.9. The pairs are either at close (sim 50-100 kpc, five pairs) or wide (sim 450-500 kpc, three pairs) angular separation and have velocity differences of $ v km $. We detected extended emission around 12 of the 14 targeted quasars and investigated the luminosity, size, kinematics, and morphology of these Lyalpha nebulae. On average, they span about 90 kpc and are 2.8 $ $ erg s$^ $ bright. Irrespective of the quasars' projected distance, the nebulae often (sim 45 <!PCT!>) extend toward the other quasar in the pair, leading to asymmetric emission whose flux-weighted centroid is at an offset position from any quasar location. We show that large nebulae are preferentially aligned with the large-scale structure, as traced by the direction between the two quasars, and conclude that the cool gas (10$^4$ K) in the CGM traces well the direction of cosmic web filaments. Additionally, the radial profile of the Lyalpha surface brightness around quasar pairs can be described by a power law with a shallower slope ($ with respect to single quasars ($ indicative of increased CGM densities out to large radii and/or an enhanced contribution from the intergalactic medium (IGM) due to the dense environments expected around quasar pairs. The sample presented in this study contains excellent targets for ultra-deep observations to directly study filamentary IGM structures in emission. This work demonstrates that a large snapshot survey of quasar pairs will pave the way to direct statistical study of the IGM.

Characteristics of Spatiotemporal Changes in China's Carbon Budget at Different Administrative Scales

Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of "double carbon" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales （provinces, cities, and counties） in China. The results showed that： ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of "high in the north and low in the south, high in the east and low in the west." ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows： In the spatial pattern of "hot in the east and cold in the west," the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that： ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions （such as different provinces） and lower-level administrative regions at another scale （such as different cities in the same province） showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination between provinces, which is expected to better promote the implementation of relevant policies.

Changes in traffic carbon emissions with traffic conditions and their control strategies

Road traffic carbon dioxide emissions have a significant impact on the atmospheric environment, and changes in traffic conditions can affect these emissions; while changes in traffic state and traffic infarction can reflect traffic conditions, there are also differences in carbon dioxide emissions generated by vehicles operating on different fuels. Therefore, this paper sequentially determines quantitative indicators of traffic states and traffic infarction as well as macro control strategies to improve traffic carbon dioxide emissions. Furthermore, taking the confluence area as the object of analysis, the impact of traffic state and traffic infarction on carbon dioxide emissions is sequentially analysed with actual traffic flow data and statistical methods, and corresponding models are constructed. Meanwhile, based on the analysis results, mainline speed limit control strategies that consider the traffic state and traffic infarction, as well as the control strategy based on the combination of multiple fuel–vehicle combinations, are presented. The analysis results show that changes in both traffic states and traffic infarction can affect traffic carbon dioxide emissions from the mainline and the on-ramps, which can fundamentally affect traffic conditions. Moreover, total carbon dioxide emissions from a combination of gasoline and diesel minibuses decrease with an increase in the ratio of gasoline minibuses.

Agricultural Productivity and Climate Mitigation

Agriculture will play a central role in meeting greenhouse gas (GHG) emission targets, as the sector currently contributes ∼22% of global emissions. Because emissions are directly tied to resources employed in farm production, such as land, fertilizer, and ruminant animals, the productivity of input use tends to be inversely related to emissions intensity. We review evidence on how productivity gains in agriculture have contributed to historical changes in emissions, how they affect land use emissions both locally and globally, and how investments in research and development (R&D) affect productivity and therefore emissions. The world average agricultural emissions intensity fell by more than half since 1990, with a strong correlation between a region's agricultural productivity growth and reduction in emissions intensity. Additional investment in agricultural R&D offers an opportunity for cost-effective (<US$30 per ton carbon dioxide) and large-scale emissions reductions. Innovations that target specific commodities or inputs could even further reduce the cost of climate mitigation in agriculture.

A comparison of meteorological normalization of PM2.5 by multiple linear regression, general additive model, and random forest methods

PM2.5 is still one of the major atmospheric pollutants worldwide. Extracting contributions of anthropogenic emission control from the observed PM2.5 variations (PM2.5_anth), which are also strongly affected by meteorological changes, is critical for effective pollution control. Statistical and machine learning methods are usually used for such purpose, but the effectiveness of these methods is hard to evaluate due to the lack of observed anthropogenic contributions. In this study, we use the chemical transport model GEOS-Chem standard simulation to mimic PM2.5 variability in the real atmosphere, and use the model simulation with fixed meteorological fields as the “true value” for PM2.5_anth. We evaluate the effectiveness of three methods in meteorological normalization of PM2.5 on decadal (2006–2017) and synoptic (one month) scale: multiple linear regression (MLR), general additive model (GAM), and random forest (RF) algorithm. For meteorological normalization of PM2.5 on decadal scale, 67–72% of the MLR simulations show positive biases and 56–75% of the RF simulations show negative biases. The “true value” of PM2.5_anth falls within the range of meteorological normalization results of the three methods in most cases, but consistent positive/negative biases are observed in ∼30% of the cases, when meteorological changes dominate PM2.5 variability. In addition, the biases are correlated to the contribution of meteorological changes. As such, multiple statistical or machine learning methods are recommended to quantify the uncertainties associated with method choice in cases anthropogenic emission changes dominate PM2.5 variability. On synoptic scale, RF performs better in reproducing the daily variations of the PM2.5_anth differences than MLR (GAM) in all (83% of) the cases, and is recommended for meteorological normalization of PM2.5 in short-term in eastern China.

Effect of Different Coating Materials on Black Périgord Truffle (Tuber melanosporum) Aroma Profile and Its Shelf Life

AbstractBlack Périgord truffles (Tuber melanosporum) are the highest-priced edible fungus in the world due to their unique flavour, rarity, short growing season, difficulty in mass cultivating, and short shelf-life. The current industrial practices have not been effective in extending truffle shelf-life while preserving its aroma profiles. This study aimed to determine the effectiveness of several preservation methods on Australian-grown black Périgord truffles, which include assessing the changes in the volatile organic compounds (VOCs) of truffles treated with edible coatings, antimicrobial agents, or antioxidants such as chitosan, gum Arabic, kafirin, natamycin, tocopherol, vitamin C, and citric acid at the interval of 0, 7, and 14 days of storage. The study also aimed to assess the capability of gamma-cyclodextrin (γ-CD) in encapsulating truffle VOCs at the intervals of 0, 14, and 28 days of storage. Among all the edible coatings, chitosan-treated truffles had the least change in VOCs, especially the black truffle aroma volatile markers, 2-methyl-1-butanal, 2,4-dithiapentane, and dimethyl sulphide. Chitosan also resulted in no significant changes (P < 0.05) in the carbon dioxide emissions of truffle. The PCA plots showed that chitosan-coated samples displayed the least changes. The sole application of antimicrobial agents or antioxidants was ineffective in delaying the deterioration process. On the other hand, the results show that γ-CD was able to encapsulate 30 truffle’s VOCs, which included 3-methyl-1-butanal, 2-methyl-1-butanol, dimethyl sulphide, and 2,4-dithiapentane with no significant changes over the storage period.