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This paper deals with incorporating thermoelectric generators into wood-fired stove to enhance energy efficiency and explore sustainable heating solutions. Wood-fired stoves are essential solutions for heating and cooking, but their conventional design poses environmental impact and efficiency challenges. By utilizing thermoelectric generators to capture waste heat, this research aims to elevate the overall performance of wood-fired stoves, reduce emissions, and optimize energy conversion. Through comprehensive experimental data and analysis, the study sheds light on the potential of thermoelectric generator integration, even in manually operated wood-fired stoves. The research stages outlined in the paper focus on selecting the most favorable conditions for thermoelectric generator installation, revealing that thermoelectric generators' highest power generation efficacy reached around 42% in a stove without an accumulation layer and slightly exceeded 30% in a stove with an accumulation layer. [ABSTRACT FROM AUTHOR]

In recent years, there has been considerable focus on ensuring that energy is used in the most efficient manner possible. This is due to the fact that globally, over 70% of energy is generated from fossil fuels. Consequently, the matter of designing and utilizing materials that will negate energy losses within the construction industry is of paramount importance. Simultaneously, the necessity for a sustainable approach to the design and production of materials is strongly emphasized. This paper presents an innovative approach to the use of a combination of mineral and plant-based fillers in polyurethane foam technology as a thermal insulation material with the potential to be used in construction to reduce energy consumption. Polyurethane composites containing fly ash from biomass combustion and the addition of rice, sunflower, and buckwheat husks as plant fillers were proposed. The structure of the obtained materials was studied, and the most important physical properties were analyzed. These included apparent density, dimensional stability, water absorption, and the effects of UV radiation and water influence on the carbon, hydrogen, nitrogen, and oxygen content. Moreover, the mechanical properties of the materials were investigated, including compressive strength and brittleness. Additionally, the foams were subjected to flammability tests using a cone calorimeter. Furthermore, additional parameters were determined, including the limiting oxygen index and the vertical and horizontal flammability tests. The results demonstrate the beneficial effects of combining mineral and vegetable fillers in polyurethane foam. [ABSTRACT FROM AUTHOR]

During biomass combustion in a grate-fired boiler, each particle undergoes a sequence of different reactions, and the phenomena differ from the conversion of a single, thermally thin, particle. Hence, this paper aims to deepen the understanding of biomass conversion processes and provides valuable insights for advancing biomass-based energy systems. Firstly, the weight loss characteristics of the larger particles of eucalyptus, pine, acacia, and olive samples were investigated at different isothermal temperatures in a purpose-built reactor that simulates the devolatilization process in a controllable manner. As opposed to the thermogravimetric analysis using thermally thin particles, it was concluded that all fuels show that the combustion of large particles does not exhibit separate consecutive conversion stages, due to internal diffusion resistance. Furthermore, it was verified that the devolatilization rate depends mainly on the reactor temperature, and, consequently, the mass-loss profile is independent of the biomass type. In addition to these experiments, the composition of the gases over the devolatilization period was analyzed for the main fuel used in power plants, eucalyptus. Once again, a strong correlation to the reactor temperature was observed, with CO2 and CO always being the main devolatilization products. The temperature dependence of both compounds presented an increase from 8 to 13% between 600 and 800 °C for CO, while the CO2 yield only slightly increased from 11 to 12%. These observations were essential to identify the transport phenomena effect and the gaseous products released during the biomass combustion. [ABSTRACT FROM AUTHOR]

As an emerging environmentally friendly fuel, biodiesel has excellent fuel properties comparable to those of petrochemical diesel. Oleic acid methyl ester, as the main component of biodiesel, has the characteristics of high cetane number and low emission rate of harmful gases. However, the comprehensive chemical conversion pathway of oleic acid methyl ester is not clear. In this paper, the reactive force field molecular dynamics simulation (ReaxFF-MD) method is used to construct a model of oleic acid methyl ester pyrolysis and combustion system. Further, the chemical conversion kinetics process at high temperatures (2500 K–3500 K) was studied, and a chemical reaction network was drawn. The research results show that the density of the system has almost no effect on the decomposition activation energy of oleic acid methyl ester, and the activation energies of its pyrolysis and combustion processes are 190.02 kJ/mol and 144.89 kJ/mol, respectively. Ethylene, water and carbon dioxide are the dominant and most accumulated products. From the specific reaction mechanism, the main pyrolysis path of oleic acid methyl ester is the breakage of the C-C bond to produce small molecule intermediates, and subsequent transformation of the ester group radical into carbon oxides. The combustion path is the evolution of long-chain alkanes into short-carbon-chain gaseous products, and these species are further burned to form stable CO2 and H2O. This study further discusses the microscopic combustion kinetics of biodiesel, providing a reference for the construction of biodiesel combustion models. Based on this theoretical study, the understanding of free radicals, intermediates, and products in the pyrolysis and combustion of biomass can be deepened. [ABSTRACT FROM AUTHOR]

Ion chromatography and related techniques have been the most popular separation methods used in the determination of organic and inorganic anions and cations, predominantly in water and wastewater samples. Making progress in their development and introducing new stationary phases, methods of detection and preparation of samples for analyses have given rise to the broadening of their analytical range. Nowadays, they are also used for substances that are not ionic by nature but can convert to such forms under certain conditions. These encompass, among others, carbohydrates, whose role and significance in humans' lives and environment is invaluable. Their presence in the air is mostly due to the industrial burning of biomass for energy production purposes. In addition, the content of sugars in plants, fruits and vegetables, constituting the base of human diets, affects our health condition. Given that, there is not only a need for their determination by means of routine methods but also for searching for novel analytical solutions. Based on literature data from the past decade, this paper presents the possibilities and examples of applications regarding ion chromatography and related techniques for the determination of carbohydrates in environmental samples, biomass and plants constituting food or raw materials for food production. Attention has been paid to the virtues and limitations of the discussed separation methods in this respect. Moreover, perspectives on their development have been defined. [ABSTRACT FROM AUTHOR]

The assumptions of contemporary energy policies are increasing the share of renewable energy sources. Biomass combustion is developing as an alternative to fossil fuels. However, it faces challenges such as limited corrosion resistance of steel boiler components due to chloride compounds in flue gases and fly ash. This paper provides a comprehensive thermodynamic analysis of chloride-induced corrosion in steel in the Fe-O-Cl-Na environment, focusing on the influence of steam concentration in the gas phase. The study was performed by using the general thermodynamic rules, the thermodynamic properties of the pure components involved in the reaction, and the properties of the solutions formed in the liquid and gas phases. The study also examined the impact of alkali metal chlorides, particularly NaCl, on the formation of NaFeO2 in the passive oxide scale layer Fe3O4/Fe2O3. Furthermore, it investigated the condensation of NaCl vapour formation of low-melting eutectic mixtures in deposits and the resulting consequences on the corrosion process. The role of HCl in the chlorination and oxidation process of steel in melted ash deposits was also discussed. The presented thermodynamic analysis was compared with assumptions of an "active oxidation" model. This study can be a valuable resource for experimental research planning and a guide for preventing corrosion in industrial settings. [ABSTRACT FROM AUTHOR]

This paper includes a discussion of the results of tests concerning changes in the thermal and emission parameters of a boiler fuelled with wood biomass under the influence of air gradation in the combustion process. The test results ensure insight into the combustion process of wood biomass with air gradation, which significantly affected the operation of the device, increasing the mass concentration of the emitted nitrogen oxide (NOx) by combustion temperature lowering, especially in the afterburning zone. The authors observed an increase in the emission of particulate matter (PM) and carbon monoxide (CO) related to the change in the combustion process stoichiometry. The tests were carried out with the use of a heating boiler equipped with an automatic pellet burner. Apart from the mass concentration measurement of the pollution emitted, the tests focused on the measurements of temperature and oxygen levels in the flue gas. The objective of the tests was to confirm the applicability of the air gradation techniques in biomass combustion in order to reduce the emission of harmful substances from heating boilers, which is a technique that has recently been used in this group of devices. The test results obtained confirm the necessity for reorganising the technical systems of the currently used pellet burners and implementing further empirical tests. [ABSTRACT FROM AUTHOR]

The characteristics of South American biomass burning (BB) aerosols transported over northern and central Argentina were investigated from July to December 2019. This period was chosen due to the high aerosol optical depth values found in the region and because simultaneously intensive biomass burning took place over the Amazon. More specifically, a combination of remote sensing observations with simulated air parcel back trajectories was used to link the optical and physical properties of three BB aerosol events that affected Pilar Observatory (PO, Argentina, 31°41′S, 63°53′W, 338 m above sea level), with low-level atmospheric circulation patterns and with types of vegetation burned in specific fire regions. The lidar observations at the PO site were used for the first time to characterize the vertical extent and structure of BB aerosol plumes as well as their connection with the planetary boundary layer, and dust particles. Based mainly on the air-parcel trajectories, a local transport regime and a long transport regime were identified. We found that in all the BB aerosol event cases studied in this paper, light-absorbing fine-mode aerosols were detected, resulting mainly from a mixture of aging smoke and dust particles. In the remote transport regime, the main sources of the BB aerosols reaching PO were associated with Amazonian rainforest wildfires. These aerosols were transported into northern and central Argentina within a strong low-level jet circulation. During the local transport regime, the BB aerosols were linked with closer fires related to tropical forests, cropland, grassland, and scrub/shrubland vegetation types in southeastern South America. Moreover, aerosols carried by the remote transport regime were associated with a high aerosol loading and enhanced aging and relatively smaller particle sizes, while aerosols associated with the local transport pattern were consistently less affected by the aging effect and showed larger sizes and low aerosol loading. [ABSTRACT FROM AUTHOR]

Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 Wm-2. Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper. [ABSTRACT FROM AUTHOR]

From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between RemoTAP and GRASP AOD of 0.12 and 0.038 over land and ocean, respectively. The largest differences occur over the biomass burning region in equatorial Africa. The global mean values are virtually unbiased with respect to each other. For AE the RMSD between RemoTAP and GRASP is 0.33 over land and 0.23 over ocean. For SSA, we find much better agreement over land (bias = - 0.01, RMSD = 0.043 for retrievals with AOD > 0.2) than over ocean (bias = 0.053, RMSD = 0.074). As expected, the differences increase towards low AOD, over both land and ocean. We also compared the GRASP and RemoTAP AOD and AE products against MODIS. For AOD over land, the agreement of either GRASP or RemoTAP with MODIS is worse than the agreement between the two PARASOL algorithms themselves. Over ocean, the agreement is very similar among the three products for AOD. For AE, the agreement between GRASP and RemoTAP is much better than the agreement of both products with MODIS. The agreement of the latest product versions with each other and with AERONET improved significantly compared to the previous version of the global products of GRASP and RemoTAP. The results demonstrate that the dedicated effort in algorithm development for multi-angle polarimetric (MAP) aerosol retrievals still leads to substantial improvement of the resulting aerosol products, and this is still an ongoing process. [ABSTRACT FROM AUTHOR]

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m−3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m−3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020–2021. Despite a 22~62% decline in NOx levels in 2020–2021, the increased O3 caused a similar NO3− concentration (20.69~23.00 μg m−3) in 2020–2021 to that (22.93 μg m−3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019–2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future. [ABSTRACT FROM AUTHOR]

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Emissions and atmospheric concentrations of CH4 continue to increase, maintaining CH4 as the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the factors explaining the well-observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in-situ and greenhouse gas observing satellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land-surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full datasets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this edition benefits from important progress in estimating inland freshwater emissions, with better accounting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double accounting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double accounting that still exists (average of 23 Tg CH4 yr-1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr-1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr-1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr-1 or ~65 % are attributed to direct anthropogenic sources in the fossil, agriculture and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr-1or 63–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr-1 (range 9–40). Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr-1) larger global emissions (669 Tg CH4 yr-1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr-1 in Saunois et al. (2016, 2020), respectively), and for the first time uncertainty in bottom-up and top-down budgets overlap. The latitudinal distribution from atmospheric inversion-based emissions indicates a predominance of tropical and southern hemisphere emissions (~65 % of the global budget, <30° N) compared to mid (30° N–60° N, ~30 % of emissions) and high-northern latitudes (60° N–90° N, ~4 % of global emissions). This latitudinal distribution is similar in the bottom-up budget though the bottom-up budget estimates slightly larger contributions for the mid and high-northern latitudes, and slightly smaller contributions from the tropics and southern hemisphere than the inversions. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. We identify five major priorities for improving the CH4 budget: i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; ii) further development of process-based models for inland-water emissions; iii) intensification of CH4 observations at local (e.g., FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; iv) improvements of transport models and the representation of photochemical sinks in top-down inversions, and v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024). [ABSTRACT FROM AUTHOR]

This paper follows a practical approach to evaluate particulate matter emissions from biomass-fuelled power plants and analysis measurement uncertainties. Sixty-seven measurement reports from 11 biomass power plants, all equipped with fabric filters as dust control device, were analysed. Particulate matter emission measurements by gravimetrical standard reference method were chosen to provide the most reliable values to investigate the influence of bag filter parameters, such as media age or bag filter length. 92.1% of total dust emission measurements were below lower BAT-associated emission levels (BAT-AELs) for waste incineration. Data also showed that bag filter media older than 6 years can still secure very low dust emission levels. This work also gives a summary of findings and problems with uncertainty of automated measuring systems for dust emissions in biomass combustion applications in practice and quality assurance level one (QAL1) process related to very low emission levels such as lower best available techniques reference document (BREF) values. Practical examples on issues of continuous dust emission monitoring devices are also given. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of wildfire is crucial for developing management and intervention strategies. Mathematical and computational models can be used to improve our understanding of wildfire processes and dynamics. This paper presents a systematic study of a widely used advection–diffusion–reaction wildfire model with non-linear coupling. The importance of single mechanisms is discovered by analysing hierarchical sub-models. Numerical simulations provide further insight into the dynamics. As a result, the influence of wind and model parameters such as the bulk density or the heating value on the wildfire propagation speed and the remaining biomass after the burn are assessed. Linearisation techniques for a reduced model provide surprisingly good estimates for the propagation speed in the full model. • The hierarchy of the mechanisms of an advection-diffusion-reaction wildfire model is examined analytically and numerically. • In the model, decreasing the initial biomass reduces wildfire propagation speed, with minimal effect on final biomass. • Linearisation techniques provide good approximations of the wildfire propagation speed. • The spatially lumped model provides a good prediction of the terminal biomass. [ABSTRACT FROM AUTHOR]

Rural fires are currently one of the main global disasters, and Portugal is among the countries that have suffered from them for decades. These fires pose economic, environmental, and social threats to the country. A primary cause of rural fires is the burning of biomass to clear agroforestry residues. Thus, combating rural fires requires more effective forest management, particularly the removal of forest residues that serve as fuel. These residues, also known as biomass, have significant potential for energy production and biofuel use. This paper proposes a model that integrates the PROMETHEE decision-making method with the roadmapping. This proposed model includes 7 steps, including the planning of the roadmap, the definition of the decision problem, gathering information and building the roadmap. The proposed model was applied to develop a roadmap proposal for the recovery of surplus agroforestry biomass in Portugal, identifying the most emerging conversion technologies in the national context. With the roadmap developed, it was possible to understand that the recovery of surplus agroforestry biomass in Portugal involves several sectors. The energy sector is one of those that can benefit from the recovery of leftover agroforestry biomass, both from the point of view of carbon neutrality and energy independence. Forestry management is another of the great advantages of recovering leftover forestry biomass and, consequently, reducing the number of fires. In the context of recovery, combustion is the most widely used technology for producing energy or heat. The technology identified as most emerging in the upcoming years is gasification. Investment in scientific research is essential for the success of this sector, as is the development of public incentive policies and more engagement from all stakeholders. This paper conclude that valorizing agroforestry residues can reduce rural fire risks while promoting energy independence, sustainable regional development, and innovation in Portugal. • The paper proposes an integrated PROMETHEE II-Roadmap model. • The proposed model is applied to the valorization of residual agroforestry biomass in Portugal (RAFB). • Benefits of RAFB valorization include reduction of rural fires, increased renewable energy alternatives, and sustainable regional development. • An evaluation of biomass conversion technologies is performed, and gasification is identified as the most emerging. • The paper emphasizes the need in the sector for research investment, stakeholder engagement and development of supply chains. [ABSTRACT FROM AUTHOR]

In this paper, we applied the Dispersion Normalised Positive Matrix Factorisation (DN-PMF) approach recently proposed in the literature to provide a more realistic picture of the relative importance of emission strength vs. atmospheric dispersion conditions. The disentanglement of such effects is of great concern in pollution hot spots like the Po Valley (Italy), where particulate matter limit values are exceeded despite the existing abatement measures. To explore the potentiality of the DN-PMF approach – still scarcely applied in the literature – a well-chemically characterised PM 1 (atmospheric particles with aerodynamic diameter <1 μm) dataset comprising samples collected at different time resolutions at an urban background site (Bologna) in the southern Po Valley was used. Indeed, it is well known that shallow mixing layers promote pollutant accumulation but this observation is not enough to exclude an enhancement of emission strength which could be tackled by appropriate abatement strategies. The source apportionment of sub-micron sized aerosols having a quite long atmospheric residence time in a complex environment like the Po Valley - which is also strongly impacted by secondary aerosol formation on a basin-scale - is generally quite challenging when using receptor models. Due to the availability of a huge dataset with variables having multiple time resolutions, in this work the DN-PMF was implemented in a multi-time resolution approach (MT) to achieve a better source identification and to gain knowledge about the relative importance of atmospheric dilution vs. emissions. A comparison between results obtained by the application of the regular multi time resolution (REG-MT) vs. the DN-MT approach is presented here for the five factors identified (nitrate-dominated, sulphate-dominated, biomass burning, mineral dust, and urban aerosol). The first interesting outcome is that REG-MT and DN-MT results do not point at significant differences in temporal patterns for aerosol components and sources impacting at the basin-scale (i.e. sulphate- and nitrate-dominated aerosol, biomass burning) thus suggesting that the diel modulation of these PM 1 emissions is somehow masked by the stronger variability of the mixing layer. Conversely, contributions from local sources with more pronounced diel variation like traffic are quite well reproduced by DN-MT and the ambient concentrations are enhanced compared to REG-MT. This is an important piece of information highlighting that PM 1 concentrations from local sources have been likely underestimated by REG-MT assessments. To our knowledge, this is one of the very few applications of DN-MT and the first one at a European site where the huge effort made to implement air pollution containment measures is still not very much effective in reducing PM levels; moreover, in this paper a detailed discussion about the possible interpretation of the output of DN-MT in terms of temporal patterns is reported. [Display omitted] • High PM levels are due to atmospheric stability and emission strength; DN-PMF points out the source emission role. • Secondary aerosol-dominated factors showed a regional nature. • Urban aerosol factor was highly enhanced by dispersion-normalisation. [ABSTRACT FROM AUTHOR]

On the international level, it is common to act on reducing emissions from energy systems. However, in addition to industrial emissions, low-stack emissions also make a significant contribution. A good step in reducing its environmental impact, is to move to biofuels, including biomass. This paper examines the impact of placing a catalytic system in a retort boiler to minimize emissions of greenhouse gases, dust and other pollutants when burning pellets. The effect of platinum, and oxides of selected metals placed on the deflector as a solid catalyst was studied. Based on the experimental data, a branched artificial neural network was constructed and trained. The routing of three parallel topologies made it possible to achieve high accuracy while keeping the input data relatively simple. The system showed an average error of 3.54% against arbitrary test data. On the basis of experimental data as well as predictions returned by the artificial neural network, recommendations were shown for the catalysts used and their amounts. Depending on the biomass from which the pellet was produced, the experiment suggested the use of titanium or copper oxides. In the case of the neural network, it was able to select a better system, based on platinum, improving emission reductions by up to more than 19%, depending on the type of pellet used. [Display omitted] • Unique three-path-ANN system to simulate catalytic biomass combustion. • High accuracy with MRE of 3.54 % versus unbiased test data. • Bioenergy production from straw, hemp and wood pellets. • Complexed system to forecast 11 different parameters. • Case study indicates optimal catalyst – feedstock pairs. [ABSTRACT FROM AUTHOR]

Exact and trusty prediction of pollutant emissions is pivotal for optimal combustion control in biomass cogeneration systems, which possess multiple variables, high-volume data streams, and dynamic characteristics. Aiming at the multivariate dynamic systems, this paper extends a classical fast relevance vector regression (FRVR) algorithm into a multivariate form to accomplish synchronous multi-pollutant prediction. Meanwhile, a flexible and effective online training strategy is proposed to solve the problems of low accuracy of multi-step prediction and lack of dynamic updating capability. First, the given dataset is divided utilizing the k -means clustering method to enhance the clustering of similar features and expedite the prediction process. Then, the classical FRVR algorithm is extended into a multiple-output form, enabling the simultaneous prediction of multiple pollutant emissions. Moreover, the incremental learning method is introduced into the proposed multivariate FRVR model to improve its dynamic performance and online learning ability. Finally, the proposed method's effectiveness is verified through a biomass cogeneration systems case. Experimental findings fully illustrate that the proposed method provides the lower RMSE and MAE while runtime decreases by 50% and R 2 reaches 96%. The proposed method significantly outperforms others, showing excellent potential in the pollutant prediction field. • An IMFRVR algorithm is proposed to predict multiple pollutant concentrations. • The k -means method cluster the data to extract useful information from the original data. • The MFRVR model is built by setting a Gaussian distribution to the FRVR weight matrix. • The incremental learning algorithm is employed to update prediction model dynamically. [ABSTRACT FROM AUTHOR]

Frequent forest fires severely damage forest ecosystems. One potential big issue, however, is the fact that the substantial release of greenhouse gases (GHGs) from biomass combustion significantly impacts the global climate system and carbon balance. This study aims to assess the emissions of major carbon-containing gases from forest fires in mainland China between 2011 and 2021. Information on wildfires was obtained with Google Earth Engine (GEE) through the integration of MODIS products and Global Forest Above Ground Biomass (AGB) produced by the Climate Change Initiative Biomass (CCI BIOMASS) Programme. Utilizing the combustible load model and consideration of carbon emission factors in different vegetation, from 2011 to 2022, mainland China consumed an estimated 35.55 Tg C (3.23 Tg C yr−1) of above-ground combustible matter, resulting in 46.94 Tg (4.27 Tg yr−1) of carbon-containing gas emissions. Among these emissions, 42.16 Tg (3.83 Tg yr−1), 4.58 Tg (0.42 Tg yr−1), and 0.20 Tg (0.02 Tg yr−1) were attributed to CO 2 , CO, and CH 4. In general, carbon emissions from forest fires in mainland China exhibited a declining pattern with fluctuations. This indicates a substantial decrease in average annual emissions of CO 2 and CH 4 by 48.38% and 88.87%, respectively, compared to the previous century (1990s). Additionally, there was an average annual decrease in biomass consumption of approximately 35.4%. When analyzing the results on regional scales using linear regression and normalization methods, it was found that 81%–84% of provinces and regions in mainland China showed a decline in forest fire carbon emissions. Nevertheless, several areas in the northwest region displayed a noticeable rising trend. Pixel analysis is utilized in this paper to perform a spatial analysis of carbon emissions and fire locations associated with forestry fires in mainland China. This analysis clarifies the impact of combustible load distribution across different fire intensities on the interannual variability of carbon emissions from wildfires, thereby offering fire management authorities valuable insights. • Estimated carbon-containing gas emissions from wildfires in Mainland China at a pixel level in 2011–2021. • Compared 11-year average annual wildfire emissions with data from the previous century. • Explored the interrelationships among wildfire points, burnt area, net primary productivity, and fuel load. • Analyzed emission trends of major carbon gases from wildfires in Mainland China. [ABSTRACT FROM AUTHOR]

Open biomass burning (OBB) significantly affects regional and global air quality, the climate, and human health. The burning of forests, shrublands, grasslands, peatlands, and croplands influences OBB. A global emissions inventory based on satellite fire detection enables an accurate estimation of OBB emissions. In this study, we developed a global high-resolution (1km×1km) daily OBB emission inventory using the Chinese Fengyun-3D satellite's global fire spot monitoring data, satellite-derived biomass data, vegetation-index-derived spatiotemporally variable combustion efficiencies, and land-type-based emission factors. The average annual estimated OBB emissions for 2020–2022 were 2586.88 Tg C, 8841.45 Tg CO2 , 382.96 Tg CO, 15.83 Tg CH4 , 18.42 Tg NOx , 4.07 Tg SO2 , 18.68 Tg particulate organic carbon (OC), 3.77 Tg particulate black carbon (BC), 5.24 Tg NH3 , 15.85 Tg NO2 , 42.46 Tg PM 2.5 and 56.03 Tg PM 10. Specifically, taking carbon emissions as an example, the average annual estimated OBBs for 2020–2022 were 72.71 (Boreal North America, BONA), 165.73 (Temperate North America, TENA), 34.11 (Central America, CEAM), 42.93 (Northern Hemisphere South America, NHSA), 520.55 (Southern Hemisphere South America, SHSA), 13.02 (Europe, EURO), 8.37 (Middle East, MIDE), 394.25 (Northern Hemisphere Africa, NHAF), 847.03 (Southern Hemisphere Africa, SHAF), 167.35 (Boreal Asia, BOAS), 27.93 (Central Asia, CEAS), 197.29 (Southeast Asia, SEAS), 13.20 (Equatorial Asia; EQAS), and 82.38 (Australia and New Zealand; AUST) TgCyr-1. Overall, savanna grassland burning contributed the largest proportion of the annual total carbon emissions (1209.12 TgCyr-1 ; 46.74 %), followed by woody savanna/shrubs (33.04 %) and tropical forests (12.11 %). SHAF was found to produce the most carbon emissions globally (847.04 TgCyr-1), followed by SHSA (525.56 TgCyr-1), NHAF (394.26 TgCyr-1), and SEAS (197.30 TgCyr-1). More specifically, savanna grassland burning was predominant in SHAF (55.00 %, 465.86 TgCyr-1), SHSA (43.39 %, 225.86 TgCyr-1), and NHAF (76.14 %, 300.21 TgCyr-1), while woody savanna/shrub fires were dominant in SEAS (51.48 %, 101.57 TgCyr-1). Furthermore, carbon emissions exhibited significant seasonal variability, peaking in September 2020 and August of 2021 and 2022, with an average of 441.32 TgCmonth-1 , which is substantially higher than the monthly average of 215.57 TgCmonth-1. Our comprehensive high-resolution inventory of OBB emissions provides valuable insights for enhancing the accuracy of air quality modeling, atmospheric transport, and biogeochemical cycle studies. The GEIOBB dataset can be downloaded at http://figshare.com (last access: 30 July 2024) with the following DOI: 10.6084/m9.figshare.24793623.v2 (Liu et al., 2023). [ABSTRACT FROM AUTHOR]

Numerous studies have investigated the long-term variability in surface solar radiation (SSR) around the world. However, the large disparity in the availability of observational data between developed and less developed/developing countries leads to an under-representation of studies on SSR changes in the latter. This is especially true for South America, where few observational studies have investigated the SSR trends and usually only at a local or regional scale. In this study we use data from 34 stations distributed throughout all of the regions of Brazil to present the SSR trends in the first 2 decades of the 21st century and investigate their associated causes. The stations were grouped into eight composites according to their proximity. Our results show that in north and northeast Brazil a strong dimming occurred, with significant contributions from increasing atmospheric absorption, most likely due to anthropogenic emissions, and increasing cloud cover. In the southeast and midwest regions of Brazil, near-zero trends resulted from competing effects of clear-sky processes (attenuation of solar radiation under cloudless conditions) and strong negative trends in cloud cover. In the southern part of the Amazon and in south Brazil a statistically insignificant brightening was observed, with significant contributions from decreasing biomass burning emissions in the former and competing minor contributions in the latter. These results can help deepen our knowledge and understanding of SSR long-term trends and their causes in South America, reducing the under-representation of this continent when compared with regions like Europe. [ABSTRACT FROM AUTHOR]

The tropospheric hydroxyl (TOH) radical is a key player in regulating oxidation of various compounds in Earth's atmosphere. Despite its pivotal role, the spatiotemporal distributions of OH are poorly constrained. Past modeling studies suggest that the main drivers of OH, including NO 2 , tropospheric ozone (TO 3), and H 2 O(v), have increased TOH globally. However, these findings often offer a global average and may not include more recent changes in diverse compounds emitted on various spatiotemporal scales. Here, we aim to deepen our understanding of global TOH trends for more recent years (2005–2019) at 1×1 °. To achieve this, we use satellite observations of HCHO and NO 2 to constrain simulated TOH using a technique based on a Bayesian data fusion method, alongside a machine learning module named the Efficient CH 4 -CO-OH (ECCOH) configuration, which is integrated into NASA's Goddard Earth Observing System (GEOS) global model. This innovative module helps efficiently predict the convoluted response of TOH to its drivers and proxies in a statistical way. Aura Ozone Monitoring Instrument (OMI) NO 2 observations suggest that the simulation has high biases for biomass burning activities in Africa and eastern Europe, resulting in a regional overestimation of up to 20 % in TOH. OMI HCHO primarily impacts the oceans, where TOH linearly correlates with this proxy. Five key parameters, i.e., TO 3 , H 2 O(v), NO 2 , HCHO, and stratospheric ozone, can collectively explain 65 % of the variance in TOH trends. The overall trend of TOH influenced by NO 2 remains positive, but it varies greatly because of the differences in the signs of anthropogenic emissions. Over the oceans, TOH trends are primarily positive in the Northern Hemisphere, resulting from the upward trends in HCHO, TO 3 , and H 2 O(v). Using the present framework, we can tap the power of satellites to quickly gain a deeper understanding of simulated TOH trends and biases. [ABSTRACT FROM AUTHOR]

Nowadays, almost all countries in the world are intensifying their search for locally available energy sources to become independent of external supplies. The production of alternative fuels from biomass and waste by thermal treatment or direct use in the combustion process is still the simplest method for fast and cheap heat production. However, the different characteristics of these fuels can cause problems in the operation of the plants, resulting in increased air pollution. Therefore, the analysis of the thermal treatment of solid fuels is still an important issue from a practical point of view. This work aimed to study biomass combustion in a small-scale reactor using the in-house Extended DEM (XDEM) method based on mixed Lagrangian–Eulerian approaches. This was provided by a novel, independently developed coupling computational interface. This interface allows for a seamless integration between CFD and DEM, improving computational efficiency and accuracy. In addition, significant advances have been made in the underlying physical models. Within the DEM framework, each particle undergoes the thermochemical processes, allowing for the prediction of its shape and structural changes during heating. Together, these changes contribute to a more robust and reliable simulation tool capable of providing detailed insights into complex multi-phase flows and granular material behavior. Numerical results were obtained for a non-typical geometry to check the influence of the walls on the distribution of the parameters in the reactor. The results show that XDEM is a very good tool for predicting the phenomena during the thermal treatment of solid fuels. In particular, it provides information about all the moving particles undergoing chemical reactions, which is very difficult to obtain from measurements. [ABSTRACT FROM AUTHOR]

This study aims to delineate the characteristics of black carbon (BC) in the atmosphere over the urban background environment in Vilnius (Lithuania) from 1 June 2021 to 31 May 2022 using aethalometer (Magee Scientific) measurements. The annual mean concentrations of BC originating from fossil fuels (BCff) and from biomass burning (BCbb) were found to be 0.63 μg m−3 with a standard deviation (SD) of 0.67 μg m−3 and 0.27 µg m−3 (0.35 μg m−3). The further findings highlight the dominance of fossil-fuel-related BC throughout the study period (71%) and the seasonal variability of BC pollution, with biomass-burning-related BC making the largest contribution during the summer season (41%) and the smallest contribution during autumn (23%). This information provides valuable insights into the sources and dynamics of BC pollution in the region. The sources and composition of BC on the days with the highest pollution levels were influenced by a combination of local and regional factors in every season. Additionally, this study employs an advanced approach to understanding urban BC pollution by focusing on high-pollution days (18), identified based on a daily mean BC mass concentration exceeding the 95th percentile, alongside an analysis of overall seasonal and diurnal variations. This methodology surpasses many those of previous urban BC studies, offering a comprehensive examination of the sources and composition of BC pollution. [ABSTRACT FROM AUTHOR]

The proposed study is devoted to highlighting the importance of mixed oxides preparation through the layered double hydroxide route for undesirable gas pollutants abatement. Different series of Cu/Al/Ce mixed oxides with similar or different stoichiometrics were prepared and compared for toluene and/or CO oxidation. Catalyst synthesis methods influence material properties and activity for oxidation reactions. The high activity for the oxidation reactions of mixed oxides derived from LDH is explained by the Cu/Ce synergy. The presence of CO in the CO/toluene mixture does not affect the total toluene oxidation, and the toluene does not affect the total oxidation of CO conversion at low temperatures. The most effective catalytic material (Cu6Al1.2Ce0.8) presents a long lifetime stability for total toluene oxidation and resistance to CO poisoning in mixtures. [ABSTRACT FROM AUTHOR]

In this article, we describe multiannual variations of the atmospheric aerosol optical depth values in the widely understood area of the Baltic Sea. We present the trends in the changes and depict unusual aerosol situations. As a result of analyses, we focus on 2019, since unusually high values of aerosol optical depth were recorded in several stations around the Baltic. We match the high aerosol levels with an unusually high number of wildfires across Europe in spring and summer, which emitted large quantities of aerosols into the atmosphere that were distributed over vast European areas in part by the wind. We then connect this case with the climate change consequences. Since aerosols influence the radiative budget of the planet by directly affecting the atmospheric radiation budget, it is obvious that human well-being is in danger due to wildfires, as well as from the atmospheric perspective. Climate change will lead to more frequent fires; thus, humans need to develop solutions to decrease the risk of fire outbreaks. [ABSTRACT FROM AUTHOR]

During the 2020 austral summer, the pristine atmosphere of the southwest Indian Ocean (SWIO) basin experienced significant perturbations. This study examines the variability of aerosols and carbon monoxide (CO) over this remote oceanic region and investigates the underlying processes in the upper troposphere–lower stratosphere (UT-LS). Aerosol profiles in January and February 2020 revealed a multi-layer structure in the tropical UT-LS. Numerical models – the FLEXible PARTicle dispersion model (FLEXPART) and the Modèle Isentropique de transport Mésoéchelle de l'Ozone Stratosphérique par Advection (MIMOSA) – indicated that the lower-stratospheric aerosol content was influenced by the intense and persistent stratospheric aerosol layer generated during the 2019–2020 extreme Australian bushfire events. A portion of this layer was transported eastward by prevailing easterly winds, leading to increased aerosol extinction profiles over Réunion on 27 and 28 January. Analysis of advected potential vorticity revealed isentropic transport of air masses containing Australian biomass burning aerosols from extratropical latitudes to Réunion at the 400 K isentropic level on 28 January. Interestingly, we found that biomass burning (BB) activity in eastern Africa, though weak during this season, significantly influenced (contributed up to 90 % of) the vertical distribution of CO and aerosols in the upper troposphere over the SWIO basin. Ground-based observations at Réunion confirmed the simultaneous presence of African and Australian aerosol layers. This study provides the first evidence of African BB emissions impacting the CO and aerosol distribution in the upper troposphere over the SWIO basin during the convective season. [ABSTRACT FROM AUTHOR]

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is coincident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here, we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize covariations in humidity and BB smoke across the SEA. The observed plume–vapor relationship, and its agreement with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between carbon monoxide (CO) and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k -means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts as they covary. While the humidity profiles show a range in both total water vapor concentration and in vertical structure, the CO profiles primarily vary in terms of maximum concentration, with similar vertical structures in each. The distribution of profile types varies spatiotemporally across the SEA region and through the season, ranging from largely one type in the northeast and southwest to more evenly distributed between multiple types where air masses meet in the middle of the SEA. These distributions follow patterns of transport from the humid, smoky source region (greatest influence in the northeast of the SEA) and the seasonal changes in both humidity and smoke (increasing and decreasing through the season, respectively). With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA. [ABSTRACT FROM AUTHOR]

Sulfate and nitrate aerosols degrade air quality, modulate radiative forcing and the hydrological cycle, and affect biogeochemical cycles, yet their global cycles are poorly understood. Here, we examined trends in 21 years of aerosol measurements made at Ragged Point, Barbados, the easternmost promontory on the island located in the eastern Caribbean Basin. Though the site has historically been used to characterize African dust transport, here we focused on changes in nitrate and non-sea-salt (nss) sulfate aerosols from 1990–2011. Nitrate aerosol concentrations averaged over the entire period were stable at 0.59 µ g m -3 ± 0.04 µ g m -3 , except for elevated nitrate concentrations in the spring of 2010 and during the summer and fall of 2008 due to the transport of biomass burning emissions from both northern and southern Africa to our site. In contrast, from 1990 to 2000, nss-sulfate decreased 30 % at a rate of 0.023 µ g m -3 yr -1 , a trend which we attribute to air quality policies enacted in the United States (US) and Europe. From 2000–2011, sulfate gradually increased at a rate of 0.021 µ g m -3 yr -1 to pre-1990s levels of 0.90 µ g m -3. We used the Community Multiscale Air Quality (CMAQ) model simulations from the EPA's Air QUAlity TimE Series (EQUATES) to better understand the changes in nss-sulfate after 2000. The model simulations estimate that increases in anthropogenic emissions from Africa explain the increase in nss-sulfate observed in Barbados. Our results highlight the need to better constrain emissions from developing countries and to assess their impact on aerosol burdens in remote source regions. [ABSTRACT FROM AUTHOR]

Water-insoluble organic carbon (WIOC) constitutes a substantial portion of organic carbon (OC) and contributes significantly to light absorption by brown carbon (BrC), playing pivotal roles in climate forcing. China is a hotspot region with high levels of OC and BrC, but information regarding the sources and light-absorbing properties of WIOC on a national scale remains scarce. Here, we investigated the light-absorbing properties and sources of WIOC in 10 representative urban cities in China. On average, WIOC made up 33.4 ± 7.66 % and 40.5 ± 9.73 % of concentrations and light absorption at 365 nm (Abs 365) of extractable OC (EX-OC), which includes relatively hydrophobic OC (WIOC and humic-like substances, HULIS-C) and hydrophilic OC (non-humic-like substances, non-HULIS-C). The mass absorption efficiency of WIOC at 365 nm (MAE 365) was (1.59 ± 0.55 m2(gC)-1) comparable to that of HULIS (1.54 ± 0.57 m2(gC)-1) but significantly higher than non-HULIS (0.71 ± 0.28 m2(gC)-1), indicating that hydrophobic OC possesses a stronger light-absorbing capacity than hydrophilic OC. Biomass burning (31.0 %) and coal combustion (31.1 %) were the dominant sources of WIOC, with coal combustion sources exhibiting the strongest light-absorbing capacity. Moreover, employing the simple forcing efficiency (SFE 300–700nm) method, we observed that WIOC exhibited the highest SFE 300–700nm (6.57 ± 5.37 Wg-1) among the EX-OC fractions. The radiative forcing of EX-OC was predominantly contributed by hydrophobic OC (WIOC – 39.4 ± 15.5 % and HULIS – 39.5 ± 12.1 %). Considering the aromaticity, sources, and atmospheric processes of different carbonaceous components, we propose a light-absorbing carbonaceous continuum, revealing that components enriched with fossil sources tend to possess stronger light-absorbing capacity, higher aromatic levels, increased molecular weights, and greater recalcitrance in the atmosphere. Reducing fossil fuel emissions emerges as an effective means of mitigating both gaseous (CO2) and particulate light-absorbing carbonaceous warming components. [ABSTRACT FROM AUTHOR]

The Asian summer monsoon has a strong convectional component with which aerosols are able to be lifted up into the lower stratosphere. Due to usually long lifetimes and long-range transport aerosols remain there much longer than in the troposphere and are also able to be advected around the globe. Our aim of this study is a synergy between simulations by Chemical Lagrangian Model of the Stratosphere (CLaMS) and KARL (Koldewey Aerosol Raman Lidar) at AWIPEV, Ny-Ålesund in the Arctic, by comparing CLaMS results with exemplary days of lidar measurements as well as analyzing the stratospheric aerosol background. We use global three-dimensional Lagrangian transport simulations including surface origin tracers as well as back trajectories to identify source regions of the aerosol particles measured over Ny-Ålesund. We analyzed lidar data for the year 2021 and found the stratosphere generally clear, without obvious aerosol layers from volcanic eruptions or biomass burnings. Still an obvious annual cycle of the backscatter coefficient with higher values in late summer to autumn and lower values in late winter has been found. Results from CLaMS model simulations indicate that from late summer to early autumn filaments with high fractions of air which originate in South Asia – one of the most polluted regions in the world – reach the Arctic at altitudes between 360 and 380 K potential temperature. We found a coinciding measurement between the overpass of such a filament and lidar observations, and we estimated that backscatter and depolarization increased by roughly 15 % during this event compared to the background aerosol concentration. Hence we demonstrate that the Asian summer monsoon is a weak but measurable source for Arctic stratospheric aerosol in late summer to early autumn. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Various fire emission estimates for southern Africa during 2019, derived with multiple burned area data sets with resolutions ranging from 500 to 20 m, are evaluated using satellite carbon monoxide (CO) observations. Southern African emissions derived from burned area generated by 20 m Sentinel‐2 satellite imagery are up to 120% higher than other estimates because small fires are better detected with a higher‐resolution satellite instrument. A comprehensive comparison between simulated and observed atmospheric CO indicates that the Sentinel‐2 burned area data significantly improves emission estimates, with up to 15% reduction in CO concentration biases in comparison to emissions based on coarser resolution burned area data. We also found that the temporal lag between emissions and atmospheric CO concentrations during the peak fire month was related to atmospheric transport. These findings emphasize the importance of utilizing higher‐resolution satellite instruments in accurately estimating emissions and understanding the impact of small fires on global climate. Plain Language Summary: We studied how much carbon monoxide (CO) was released into the air in southern Africa due to fires. To derive CO emissions we used different remotely sensed data of area burned, with varying levels of detail, from 500 to 20 m, and used these emissions in a model to mimic atmospheric transport and chemistry of CO. We found that emissions derived from the very detailed 20‐m satellite images from Sentinel‐2 produced a similar large amount of CO in the atmosphere over southern Africa as seen by CO satellite observations. This is because the smaller fires, which are harder to spot, were detected with the 20‐m burned area satellite observations. We also found that the air movement and inflow of polluted air from outside Africa impacted the peak of air pollution. Key Points: Sentinel‐2 burned area detects small fires, resulting in up to 120% higher fire emissions compared to conventional resolution estimatesImproved fuel load modeling and new emission factors yield more trustworthy fire emissions that can be evaluated with top‐down constraintsAtmospheric modeling and TROPOMI CO observations indicate a 15% bias reduction using Sentinel‐2 burned area compared with coarser fire data [ABSTRACT FROM AUTHOR]

Compared to conventional monoethanolamine (MEA), alternative solvents are expected to substantially contribute to reduce the energy demand of postcombustion CO2 capture from flue gases. This study presents a comprehensive techno-economic analysis of a 27wt% 2-amino-2-methyl-1- propanol (AMP) + 13wt% piperazine (PZ) aqueous solution for CO2 capture, compared to a 30 wt% MEA solution. The study addresses the retrofit of a carbon capture unit to a biomass-fired combined heat and power (CHP) plant, effectively making it a bioenergy with a carbon capture and storage (BECCS) system. The treated flue gas has a flow rate of 23 tons/hour (t/h) with 11.54 vol% CO2 and a 90% capture rate is aimed for. Aspen Plus V14 was employed for process simulations. Initially, binary interaction parameters for AMP/PZ, AMP/H2O, and PZ/H2O are regressed using vapor-liquid equilibrium (VLE) data, which were retrieved from literature along with reaction kinetics. Validation of parameters from available experimental literature yields an average absolute relative deviation (AARD) of only 5.9%. Afterwards, a process simulation model is developed and validated against experimental data from a reference pilot plant, using a similar AMP/PZ blend, resulting in 5% AARD. Next, a sensitivity analysis optimizes operating conditions, including solvent rate, absorber/stripper packing heights, and stripper pressure, based on regeneration energy impact. Optimized results, compared to MEA, reveal that AMP/PZ reduces the energy consumption from 3.61 to 2.86 GJ/tCO2. The retrofitting of the capture unit onto the selected CHP plant is examined through the development of a dedicated model. Two control strategies are compared to address energy unavailability for supplying the capture unit. The analysis spans 4 months, selected to account for seasonal variations. At nominal capacity, CO2 emissions, rendered negative by biomass combustion and CO2 capture, reach a maximum of -3.4 tCO2/h compared to 0.36 tCO2/h before retrofitting. Depending on the control strategy and CHP plant operating point, the Specific Primary Energy Consumption for CO2 Avoided (SPECCA) ranges from 4.91 MJ/kgCO2 to 1.76 MJ/kgCO2. Finally, an economic comparison based on systematic methodology reveals a 7.87% reduction in capture cost favoring the AMP/PZ blend. Together, these findings highlight AMP/PZ as a highly favorable alternative solvent. [ABSTRACT FROM AUTHOR]

It is necessary to measure the mixing states of light-absorbing carbon (LAC) particles to reduce uncertainties in climate forcing due to particulate from wildfires and biomass combustion. For refractory LAC (normally called refractory black carbon; rBC), such measurements can be made using the single particle soot photometer (SP2). The SP2 measures the incandescent mass of individual particles heated by a 1064 nm laser. The SP2 also monitors single-particle light scattering from rBC plus internally mixed material (e.g., coatings of volatile particulate matter). rBC mixing states can be estimated from SP2 measurements by combining the scattering and incandescence signals. This is the basis of the published methods known as (i) scattering–incandescence lag-time, (ii) leading-edge only (LEO), and (iii) normalized derivative methods. More recently, the tandem centrifugal particle mass analyzer–single particle soot photometer (CPMA-SP2) method has been developed. The CPMA-SP2 method does not rely on the SP2 scattering signals and, therefore truly measures the rBC mass fraction, with no assumptions regarding particle composition or morphology. In this study, we provide the first quantitative comparison of the light-scattering and CPMA-SP2 methods for measuring mixing state. We discuss the upper and lower limits of detection (in terms of both rBC and coatings), temporal resolution, role of counting statistics, and errors associated with the measurements. We use a data set of atmospheric particles sampled at a regional background site (Kamloops about 350 km northeast of Vancouver, British Columbia, Canada), where the majority of rBC was emitted by seasonal wildfires. In the overall comparison of measurement methods, the CPMA-SP2 method is found to have significantly better systematic uncertainties than the light-scattering methods for wildfire smoke. For example, the light-scattering methods could not quantify coatings on half of the rBC particles, because their light-scattering signals were below the SP2 detection limit. Consequently, the bias in SP2-only estimates of rBC mixing states depends on the size distribution of the rBC particles. Although more accurate, CPMA-SP2 measurements require significantly more time to acquire, whereas SP2-only light-scattering analyses (both LEO and lag-time) can provide near real-time qualitative information representing large rBC particles. [ABSTRACT FROM AUTHOR]

Biomass burning releases large amounts of aerosols and chemical species into the atmosphere, representing a major source of air pollutants. Emissions and by-products can be transported over long distances, presenting challenges in quantification. This is mainly done using satellites, which offer global coverage and data acquisition for places that are difficult to access. In this study, ground-based observations are used to assess the abundance of trace gases and aerosols. On 24 November 2020, a significant increase in formaldehyde was observed with a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument located in Montevideo (Uruguay), and its vertical column densities reached values of 2.4×1016 molec. cm -2 , more than twice the values observed during the previous days. This was accompanied by an increase in the aerosol levels measured by an AErosol RObotic NETwork (AERONET) photometer located at the same site. The aerosol optical depth (AOD) at 440 nm reached values close to 1, an order of magnitude larger than typical values in Montevideo. Our findings indicate that the increase was associated with the passage of a plume originating from distant biomass burning. This conclusion is supported by TROPOspheric Monitoring Instrument (TROPOMI) satellite observations as well as HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) simulations. The profiles of the gases and aerosols retrieved from the MAX-DOAS observations are consistent with the HYSPLIT analysis, showing the passage of a plume over Montevideo on 24 November located at a height of ∼ 1.5 km. This corroborates the finding that biomass burning events occurring about 800 km north of Montevideo can affect the local atmosphere through long-distance emissions transport. This study underscores the potential of ground-based atmospheric monitoring as a tool for detection of such events. Furthermore, it demonstrates greater sensitivity compared to satellite when it comes to detection of relatively small amounts of carbonyls like glyoxal and formaldehyde. [ABSTRACT FROM AUTHOR]

While aqueous-phase processing is known to contribute to the formation of nitrogen-containing organic compounds (NOCs), the specific pathways involved remain poorly understood. In this study, we aimed to characterize the NOCs present in both pre-fog aerosols and fog water collected at a suburban site in northern China. Fourier-transform ion cyclotron resonance mass spectrometry was utilized to analyze the molecular composition of NOCs in both negative and positive modes of electrospray ionization (ESI - and ESI +). In both pre-fog aerosols and fog water samples, NOCs constituted a significant portion, accounting for over 60 % of all assigned formulas in ESI - and more than 80 % in ESI +. By comparing the molecular composition of NOCs originating from biomass burning, coal combustion, and vehicle emissions, we identified that 72.3 % of NOCs in pre-fog aerosols were attributed to primary anthropogenic sources (pNOCs), while the remaining NOCs were categorized as secondary NOCs formed within the aerosols (saNOCs). Unique NOCs found in fog water were classified as secondary NOCs formed within the fog water (sfNOCs). Through a comprehensive "precursor–product pair" screening involving 39 reaction pathways, we observed that the nitration reaction, the amine pathway, and the intramolecular N-heterocycle pathway of NH 3 addition reactions contributed 43.6 %, 22.1 %, and 11.6 % of saNOCs, respectively. In contrast, these pathways contributed 26.8 %, 28.4 %, and 29.7 % of sfNOCs, respectively. This disparity in formation pathways is likely influenced by the diverse precursors, the aqueous acidity, and the gas-phase species partitioning. Correspondingly, saNOCs were found to contain a higher abundance of carbohydrate-like and highly oxygenated compounds with two nitrogen atoms compared to pNOCs. Conversely, sfNOCs exhibited a higher content of lipid-like compounds with fewer oxygen atoms. These results underscore the distinct secondary processes contributing to the diversity of NOCs in aerosols and fog water, which may lead to their different climate effects. [ABSTRACT FROM AUTHOR]

This study investigates long-term changes in the shortwave direct aerosol radiative effect (DARE) at the top of the atmosphere (TOA) induced by biomass burning aerosol (BBA) transported from southern Africa to the south-eastern Atlantic (SEA) stratocumulus region during extended fire seasons. The evolution since 2002 of aerosol, cloud properties, and TOA shortwave outgoing radiation from advanced passive satellite sensors are presented, as well as the observational trend in clear-sky DAREclr and the retrieval trend in all-sky DAREall. Supplemented by chemical transport model simulations, we estimate that DAREclr has become more negative (−0.09 ± 0.06 W m−2 yr−1) due to increased aerosol presence in SEA. Meanwhile, DAREall has become more positive (+ 0.04 ± 0.15 W m−2 yr−1) due to aerosols in cloudy sky regions. This study reveals satellite capabilities in capturing complex BBA-cloud-solar radiation interactions for accurate radiative forcing estimates and projections. [ABSTRACT FROM AUTHOR]

The detection and evaluation of biomass burning and dust events are critical for understanding their impact on air quality, climate, and human health, particularly in the Mediterranean region. This research pioneers an innovative methodology that uses Sentinel-2 multispectral (MS) imagery to meticulously pinpoint and analyze long-transport dust outbreaks and biomass burning phenomena, originating both locally and transported from remote areas. We developed the dust/biomass burning (DBB) composite normalized differential index, a tool that identifies clear, dusty, and biomass burning scenarios in the selected region. The DBB index jointly employs specific Sentinel-2 bands: B2-B3-B4 for visible light analysis, and B11 and B12 for short-wave infrared (SWIR), exploiting the specificity of each wavelength to assess the presence of different aerosols. A key feature of the DBB index is its normalization by the surface reflectance of the scene, which ensures independence from the underlying texture, such as streets and buildings, for urban areas. The differentiation involves the comparison of the top-of-atmosphere (TOA) reflectance values from aerosol events with those from clear-sky reference images, thereby constituting a sort of calibration. The index is tailored for urban settings, where Sentinel-2 imagery provides a decametric spatial resolution and revisit time of 5 days. The average values of DBB achieve a 96% match with the coarse-mode aerosol optical depths (AOD), measured by a local station of the AERONET network of sun-photometers. In future studies, the map of DBB could be integrated with that achieved from Sentinel-3 images, which offer similar spectral bands, albeit with much less fine spatial resolution, yet benefit from daily coverage. [ABSTRACT FROM AUTHOR]

Estimating the source contribution to polycyclic aromatic hydrocarbons (PAHs) and nitropolycyclic aromatic hydrocarbons (NPAHs) in the atmosphere is necessary for developing effective disease control and pollution control measures. The NPAH-PAH combination method (NP method) was used to elucidate the contributions of vehicles and coal/biomass combustion to seasonal and long-term urban atmospheric particulate matter (PM)-bound Pyr and 1-NP concentrations in Kanazawa, Kitakyushu, Shenyang and Shanghai in the Western Pacific region from 1997 to 2021. Among the four cities, Kanazawa demonstrated the lowest Pyr concentration. The contribution of vehicles to Pyr before and after 2010 was 35% and 5%, respectively. The 1-NP concentration was reduced by a factor of more than 1/10. These changes can be attributed to the emission control from vehicles. Kitakyushu revealed the second-lowest Pyr and the lowest 1-NP concentrations. Coal combustion was found to be the main contributor to Pyr, while its contribution to 1-NP increased from 9% to 19%. The large contribution of coal combustion is attributed to iron manufacturers. Shenyang demonstrated the highest atmospheric Pyr concentration with its largest seasonal change. Vehicles are the largest contributors to 1-NP. However, coal combustion, including winter coal heating, contributed 97% or more to Pyr and more than 14% to 1-NP. Shanghai revealed the second-highest Pyr and 1-NP concentrations, but the former was substantially lower than that in Shenyang. Coal combustion was the major contributor, but the contribution of vehicles to Pyr was larger before 2010, which was similar to Kanazawa. [ABSTRACT FROM AUTHOR]

Despite the significant impacts of biomass burning (BB) on global climate change and regional air pollution, there is a relative lack of research on the temporal trends and geographic patterns of BB in Northeast China (NEC). This study investigates the spatial–temporal distribution of BB and its impact on the atmospheric environment in the NEC region during 2004 to 2023 based on remote sensing satellite data and reanalyzed data, using the Siegel's Repeated Median Estimator and Mann–Kendall test for trend analysis, HDBSCAN to identify significant BB change regions, and Moran's Index to examine the spatial autocorrelation of BB. The obtained results indicate a fluctuating yet overall increasing BB trend, characterized by annual increases of 759 for fire point counts (FPC) and 12,000 MW for fire radiated power (FRP). BB predominantly occurs in the Songnen Plain (SNP), Sanjiang Plain (SJP), Liaohe Plain (LHP), and the transitional area between SNP and the adjacent Greater Khingan Mountains (GKM) and Lesser Khingan Mountains (LKM). Cropland and urban areas exhibit the highest growth in BB trends, each surpassing 60% (p < 0.05), with the most significant growth cluster spanning 68,634.9 km2. Seasonal analysis shows that BB peaks in spring and autumn, with spring experiencing the highest severity. The most critical periods for BB are March–April and October–November, during which FPC and FRP contribute to over 80% of the annual total. This trend correlates with spring planting and autumn harvesting, where cropland FPC constitutes 71% of all land-cover types involved in BB. Comparative analysis of the aerosol extinction coefficient (AEC) between areas with increasing and decreasing BB indicates higher AEC in BB increasing regions, especially in spring, with the vertical transport of BB reaching up to 1.5 km. County-level spatial autocorrelation analysis indicates high–high clustering in the SNP and SJP, with a notable resurgence of autocorrelation in the SNP, suggesting the need for coordinated provincial prevention and control efforts. Finally, our analysis of the impact of BB on atmospheric pollutants shows that there is a correlation between FRP and pollutants, with correlations for PM2.5, PM10, and CO of 0.4, 0.4, and 0.5, respectively. In addition, the impacts of BB vary by region and season, with the most significant impacts occurring in the spring, especially in the SNP, which requires more attention. In summary, considering the escalating BB trend in NEC and its significant effect on air quality, this study highlights the urgent necessity for improved monitoring and strategic interventions. [ABSTRACT FROM AUTHOR]

Combustion of woody biomass in professional bioheating plants to generate heat and reduce the dust emissions from this process results in the formation of a huge mass of woody biomass ash (WBA). Due to WBA's rich chemical composition and the assumptions of the circular economy, this mineral material should be used for environmental purposes to recover valuable macro- and micronutrients. The basis of the research was a pot experiment designed to assess the effect of six doses of WBA (15, 30, 45, 60, 75, and 90 g pot−1) on the growth, development, yield, and chemical composition of corn. Each pot contained 9 kg of soil. Observations show that the use of increasing doses of WBA had a positive effect on the height of corn plants, increasing its yield by 7 to 10% but reducing the dry matter content by 0.47 to 1.37% and the leaf greenness index (SPAD). Moreover, WBA application (T1–T5 treatments) had a positive effect on the content of macroelements (N, K, Mg, Ca, and Na) in corn biomass. A significant increase in the content of K (54%), Mg (38%), Ca (43%), and Na (19%) was observed. However, at the same time, a significant increase in the content of heavy metals—Ni, Cd, and Pb—was observed. Different results were obtained for P, Zn, Cu, Cr, and Co, whose content in corn decreased after WBA application to soil. The obtained results indicate the possibility of using WBA in an environmentally friendly way. However, due to the great diversity of this material in terms of the content of undesirable heavy metals, it is necessary to optimize its dosage and monitor its chemical composition. Considering the growing number of bioheating plants in our country in recent years and the resulting increase in the amount of WBA produced, it is necessary to develop a rational and environmentally friendly method for managing them in the future. The results of our research may provide partial indications of such solutions. [ABSTRACT FROM AUTHOR]

Due to its low calorific value, abnormal phenomena such as incomplete combustion and flameout may occur during the combustion process of biomass syngas. The applicability of adding hydrogen can assist in the combustion of biomass syngas in boilers to overcome the above defects, and the effects need to be investigated. In this study, a multi-mechanism model is employed to numerically simulate the flow and combustion of a horizontal boiler burning biomass syngas. The reliability verification of the model is conducted by comparing it with the experimental results of combustion in a domestic boiler with biomass syngas. From the views of multi-fields and synergy, the effects of hydrogen addition on the thermal performance and emissions of biomass syngas are further expounded. Two scenarios are taken into consideration: hydrogen addition at a constant fuel volume flow rate and constant heat input. The result indicates that hydrogen addition significantly affects the multi-field synergy, which is advantageous for improving the heat transfer performance and combustion efficiency of biomass syngas. However, when the hydrogen addition ratio exceeds 20% at a constant fuel volume flow rate and 25% at constant heat input, its impact may be reduced. When the hydrogen content increases, the outlet temperature of the combustion chamber decreases, and pollutant emissions are effectively controlled. The turbulent kinetic energy at the reversal section decreases, and the uniformity of the flow field improves. These results provide certain guidance for the efficient utilization of biomass syngas and the operation of boilers burning biomass syngas. [ABSTRACT FROM AUTHOR]

Experimental measurements and modeling have been performed in the chimney of a biomass boiler to study the gaseous and particulate matter (PM) emissions during the combustion of wood pellets. A 10 kW boiler with an underfeed burner is equipped with different sensors located in the chimney (anemometer, thermocouples). The PM emissions were measured in the chimney through the engine exhaust particle sizer (EEPS) technique. Moreover, the gaseous emissions (CO2, CO, total hydrocarbons THC, O2) were obtained through infrared (IR) spectroscopy and flame ionization detector (FID). The emissions were recorded during the steady phase of the boiler and averaged over several tests. Four locations were investigated in the chimney to evaluate the evolution of the particle size and the potential deposition on the surface. The experimental results were compared with a CFD model with particle transportation. The modeling of turbulent flow in the chimney is based on a Reynolds-averaged Navier–Stokes (RANS) approach with turbulent viscosity closure. To account for flow anisotropy, the v 2 ¯ − f turbulence model was selected for this study. The effect of turbulent fluctuations on the discrete phase is considered by the discrete random walk (DRW) turbulent dispersion model. The results obtained provide access to the topology of the carrier phase flow as well as the complete distribution of the particle field within the chimney enclosure. Advanced measurement of pollutant emissions and modeling of the PM transportation are developed for the first time in a domestic biomass boiler operating in real conditions. Experimental results demonstrate several relevant information. The CO and THC emissions show a similar evolution versus time. The PM granulometric distribution measured along the chimney highlights the particle agglomeration phenomena. Moreover, the CFD model and experimental results give similar results in terms of flow characteristics and PM granulometry. [ABSTRACT FROM AUTHOR]

Morphological information on fine particles is essential for understanding their transport behavior in the ambient atmosphere and in the human respiratory system. More than 3000 transmission electron microscopy (TEM) images of fine particles were collected from ambient atmosphere and directly from various sources, such as diesel and gasoline engine exhaust, biomass burning, coal combustion, and road dust, and were then morphologically categorized into four major classes (spherical, agglomerate, polygonal, and dendrite). Pre-trained convolutional neural network (CNN) models (DenseNet169, InceptionV3, MobileNetV3Small, ResNet50, and VGG16) and traditional machine learning models (decision trees, random forests, and support vector machines) were trained using the classified particles. The fine-tuned CNN model (DenseNet169) having the deepest feature learning exhibited the best performance among the tested models, with an overall classification accuracy of 89% and an average per-class accuracy ranging from 84% to 97%. The reliable classification of thousands of images was performed within several minutes. The agglomerated class was the least misclassified because of its significantly different features from those of the other classes. The critical regions of the particles for classification decisions varied among the pre-trained models. Our results suggest that the pre-trained CNN models would be useful for the rapid morphological classification of a large number of fine particles. Copyright © 2024 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Large uncertainties persist within current biomass burning (BB) inventories, and the choice of these inventories can substantially impact model results when assessing the influence of BB aerosols on weather and climate. We evaluated discrepancies among BB emission inventories by comparing carbon monoxide (CO) and organic carbon (OC) emissions from seven major BB regions globally between 2013 and 2016. Mainstream bottom-up inventories, including the Fire INventory from NCAR 1.5 (FINN1.5) and Global Fire Emissions Database version 4s (GFED4s), along with the top-down inventories Quick Fire Emissions Dataset 2.5 (QFED2.5) and Visible Infrared Imaging Radiometer (VIIRS-)based Fire Emission Inventory version 0 (VFEI0), were selected for this study. Global CO emissions range from 252 to 336 Tg, with regional disparities reaching up to a 6-fold difference. Dry matter is the primary contributor to the regional variation in CO emissions (50 %–80 %), with emission factors accounting for the remaining 20 %–50 %. Uncertainties in dry matter often arise from biases in calculating bottom fuel consumption and burned area, influenced by vegetation classification methods and fire detection products. In the tropics, peatlands contribute more fuel loads and higher emission factors than grasslands. At high latitudes, increased cloud fraction amplifies the discrepancy in estimated burned area (or fire radiative power) by 20 %. The global OC emissions range from 14.9 to 42.9 Tg, exhibiting higher variability than CO emissions due to the corrected emission factors in QFED2.5, with regional disparities reaching a factor of 8.7. Additionally, we applied these BB emission inventories to the Community Atmosphere Model version 6 (CAM6) and assessed the model performance against observations. Our results suggest that the simulations based on the GFED4s agree best with the Measurements of Pollution in the Troposphere (MOPITT-)retrieved CO. While comparing the simulation with the Moderate Resolution Imaging Spectroradiometer (MODIS) and AErosol RObotic NETwork (AERONET) aerosol optical depth (AOD), our results reveal that there is no global optimal choice for BB inventories. In the high latitudes of the Northern Hemisphere, using GFED4s and QFED2.5 can better capture the AOD magnitude and diurnal variation. In equatorial Asia, GFED4s outperforms other models in representing day-to-day changes, particularly during intense burning. In Southeast Asia, we recommend using the OC emission magnitude from FINN1.5 combined with daily variability from QFED2.5. In the Southern Hemisphere, the latest VFEI0 has performed relatively well. This study has implications for reducing the uncertainties in emissions and improving BB emission inventories in further studies. [ABSTRACT FROM AUTHOR]

Nitrated aromatic compounds (NACs) and oxygenated derivatives of polycyclic aromatic hydrocarbons (OPAHs) play vital roles within brown carbon (BrC), influencing both climate dynamics and human health to a certain degree. The concentrations of these drug classes were analyzed in PM 2.5 from an urban area in Beijing during the autumn and winter of 2017 and 2018. There were four heavy haze episodes during the campaign, two of which happened prior to heating and the other two during heating. During the entire course of sampling, the mean total concentrations of the nine NACs and the eight OPAHs were 1.2–263 and 2.1–234 ng m -3 , respectively. The concentrations of both NACs and OPAHs were approximately 2–3 times higher in the heating period than before heating. For NACs, the relative molecular composition did not change significantly before and during heating, with 4-nitrocatechol and 4-nitrophenol demonstrating the highest abundance. For OPAHs, 1-naphthaldehyde was the most abundant species before and during heating, while the relative proportion of anthraquinone increased by more than twice, from 13 % before heating to 31 % during the heating. In Beijing's urban area during autumn and winter, significant sources of NACs and OPAHs have been traced back to automobile emissions and biomass burning activities. Interestingly, it was observed that the contribution from coal combustion increased notably during heating. It is worth noting that the secondary generation of BrC was important throughout the whole sampling period, which was manifested by the photochemical reaction before heating and the aqueous reaction during heating. It was further found that the haze in autumn and winter was nitrate-driven before heating and secondary organic carbon (SOC)-driven during heating, and the secondary formation of BrC increased significantly in pollution events, particularly during heating. [ABSTRACT FROM AUTHOR]

In numerous developing nations, the pervasive practice of crop residue incineration is a principal contributor to atmospheric contamination in agricultural operations. This study examines the repercussions of such biomass combustion on air quality during the autumnal harvest season, utilizing data acquired from satellite-based remote sensing of fire events and air pollution measurements. Employing wind direction information alongside difference-in-difference and fixed-effects methodologies, this investigation rectifies estimation inaccuracies stemming from the non-random distribution of combustion occurrences. The empirical findings reveal that agricultural residue burning precipitates an elevation in average PM2.5 and PM10 concentrations by approximately 27 and 22 μg/m3 during the autumnal incineration period, respectively. Furthermore, air pollution attributed to residue burning in prominent grain-producing regions exceeds the national average by approximately 40%. By integrating economic paradigms into agri-environmental inquiries, this study offers novel insights and substantiation of the environmental expenditures engendered by crop residue burning, juxtaposed with extant meteorological and ecological research findings. [ABSTRACT FROM AUTHOR]

Extreme biomass burning (BB) events, such as those seen during the 2019–2020 Australian bushfire season, are becoming more frequent and intense with climate change. Ground-based observations of these events can provide useful information on the macro- and micro-physical properties of the plumes, but these observations are sparse, especially in regions which are at risk of intense bushfire events. Satellite observations of extreme BB events provide a unique perspective, with the newest generation of geostationary imagers, such as the Advanced Himawari Imager (AHI), observing entire continents at moderate spatial and high temporal resolution. However, current passive satellite retrieval methods struggle to capture the high values of aerosol optical thickness (AOT) seen during these BB events. Accurate retrievals are necessary for global and regional studies of shortwave radiation, air quality modelling and numerical weather prediction. To address these issues, the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm has used AHI data to measure extreme BB plumes from the 2019–2020 Australian bushfire season. The sensitivity of the retrieval to the assumed optical properties of BB plumes is explored by comparing retrieved AOT with AErosol RObotic NETwork (AERONET) level-1.5 data over the AERONET site at Tumbarumba, New South Wales, between 1 December 2019 at 00:00 UTC and 3 January 2020 at 00:00 UTC. The study shows that for AOT values > 2, the sensitivity to the assumed optical properties is substantial. The ORAC retrievals and AERONET data are compared against the Japan Aerospace Exploration Agency (JAXA) Aerosol Retrieval Product (ARP), Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue over land, MODIS MAIAC, Sentinel-3 SYN and VIIRS Deep Blue products. The comparison shows the ORAC retrieval significantly improves coverage of optically thick plumes relative to the JAXA ARP, with approximately twice as many pixels retrieved and peak retrieved AOT values 1.4 times higher than the JAXA ARP. The ORAC retrievals have accuracy scores of 0.742–0.744 compared to the values of 0.718–0.833 for the polar-orbiting satellite products, despite successfully retrieving approximately 28 times as many pixels over the study period as the most successful polar-orbiting satellite product. The AHI and MODIS satellite products are compared for three case studies covering a range of BB plumes over Australia. The results show good agreement between all products for plumes with AOT values ≤ 2. For extreme BB plumes, the ORAC retrieval finds values of AOT > 15, significantly higher than those seen in events classified as extreme by previous studies, although with high uncertainty. A combination of hard limits in the retrieval algorithms and misclassification of BB plumes as cloud prevents the JAXA and MODIS products from returning AOT values significantly greater than 5. [ABSTRACT FROM AUTHOR]