Emission Sources Research Articles

Understanding the environmental footprint of a Swiss university – mobility, energy and material consumption before and during the SARS-CoV-2 pandemic

Purpose The purpose of this study was to evaluate the environmental footprint of a university of applied sciences in 2019 and 2020, including the effects of the lockdown periods. The study identified the main sources of emissions and assessed the pandemic-related effects. Design/methodology/approach Using the life cycle assessment methodology, this study analysed the university’s direct and indirect emissions during a regular year of operation (2019) and compared them with those generated during the lockdown periods in 2020. For the activity areas mobility, energy, waste, IT and paper, gastronomy and water, specific, primary bottom-up inventory data were gathered before and during the pandemic. The data were assessed with 15 environmental impact assessment methods of the environmental footprint framework. Findings The results of a regular year of operation (2019) depicted that student and employee commuting and business travel contributed with 86% largely to the total global warming potential of 2,572 t CO2-eq. The pandemic-induced changes in commuting and business travel resulted in a 60% reduction, leading to a drop to 1,075 t CO2-eq (2020). In contrast, the environmental footprint due to energy consumption remained almost on the same level, irrespective of the absences on-site in 2020. Originality/value This study has the potential to shape post-pandemic environmental efforts and policies in higher education institutions and contribute to a much-needed baseline against which mitigation efforts can be compared with. Unlike other studies, this study goes beyond the carbon footprint, expanding the discussion to additional environmental and human health impact categories by applying the environmental footprint framework.

Features of Planar Localization of Acoustic Emission Sources via the Inglada’s Triangulation Algorithm

This paper presents a methodology for enhancing the efficiency of acoustic emission (AE) source detection during planar localization using the Inglada’s algorithm. The study analyzes the main factors affecting the accuracy of AE source localization when using a standard planar localization approach. These factors include the threshold-based method of determining the signal registration time by AE sensors, which is based on detecting the moment when the rising wavefront voltage exceeds the discrimination threshold (uth), the signal sampling frequency (fd), and the influence of the medium’s dispersion properties on the attenuation of signal amplitude and wave propagation speed. To reduce the impact of these factors on the localization accuracy of AE sources, a novel methodology is proposed based on the use of correlation dependencies of AE pulse propagation speed on the amplitude of the recorded signals, as well as on accounting for the delay in the registration time of AE pulses during threshold detection. A series of preliminary experiments was conducted to implement the proposed methodology, where AE pulses were generated using an electronic simulator with a maximum amplitude level of um = 45—90 dB. The position of the AE pulse source varied in the range of 150 to 700 mm relative to the receiving sensors of the antenna array. As a result of applying the developed methodology, the probability of AE source detection increased to p = 0,71, compared to p = 0,36 when using the standard approach.

Estimating CO2 flows in urban parks: knowns and unknowns

The life cycle climate impacts of urban parks are poorly known. Whereas vegetation and soils can be carbon sinks, building products, energy use, and processes cause emissions. Several studies acknowledge the need for further assessment of urban parks, especially regarding vegetation, soil organic carbon, management and design, together with the development of supportive tools for climate-wise planning. To deepen our understanding of carbon flows of urban parks, we applied life cycle assessment (LCA) and studied the carbon dioxide (CO2) emissions and removals of five urban parks in Helsinki, Finland. The components of the parks were divided into four categories: site preparation, covering and surface structures, vegetation and growing media, and systems and installations. According to our findings, CO2 emissions ranged from 27.08 to 61.45 kgCO2e/m2 and CO2 removals from 11.35 to 16.23 kgCO2e/m2 with uncertainty. Planted woody vegetation and existing forested areas had the highest CO2 uptake among the vegetation types. Moreover, growing media caused on average 35% of total CO2 emissions. As significant volumes of growing media remain necessary to support the growth and establishment of plantings, finding less emission intensive alternatives to peat-based growing medium becomes essential. Other main emissions sources included transportation, and replacements of surface materials, but their dominance is highly dependent on the design, use and maintenance of the park. LCA offers a robust assessment framework for the quantification of greenhouse gas emissions and is evolving towards the including of greenhouse gas removals and storages. However, the inclusion of living organisms would require changes in the mindset of LCA. The level of maturity in the assessment methods differs significantly between the park components. Data and methods are especially lacking for nursery production, maintenance and end-of-life phases of vegetation, soils, and mulches. We also identified uncertainties regarding the estimations of CO2 uptake by woody vegetation, lawns, and meadows due to software limitations and lack of data for local context. Simulating dynamic plantings raises additional questions, together with the forecast of accurate meteorological conditions of a changing climate. This research highlights the need for more holistic life cycle assessment of urban parks to inform low-carbon landscape industries.

Dynamic Carbon Emission Factors in Source–Network–Storage Power System Planning: A Focus on Inverse Modelling

In light of global climate change, China has set strategic goals for carbon peaking by 2030 and carbon neutrality by 2060, emphasizing the necessity of constructing a new power system with a high proportion of renewable energy sources. As coal-fired power plants are the main carbon emissions source in the power system, their low-carbon transition and morphology structure optimization is crucial. This paper explores the critical role of dynamic carbon emission factors within source–network–storage power system planning and proposes an innovative inverse dynamic carbon emission factor that effectively captures the nonlinear relationship between load rates and emissions. Comparative analyses using the HRP-38 test case demonstrate that the inverse model enhances computational efficiency, reduces solution times, and more accurately reflects the emissions characteristics of coal-fired units across varying operational conditions. Furthermore, the inverse model offers improved economic performance and broader flexibility in unit selection, highlighting its potential to balance carbon emissions control and economic optimization in future power system planning.

THE ATTENUATION CHARACTERISTICS OF DIFFERENT FREQUENCY COMPONENTS OF ACOUSTIC EMISSION SIGNAL DURING PROPAGATION IN ELM AND PINE WOOD

In order to gain a deeper understanding of the attenuation characteristics of different frequency components of acoustic emission signal when propagating in wood, this research conduct pencil lead fracture experiments on the surface of elm and pine specimen. Original AE signals acquired by different sensors are decomposed using 5-level wavelet transform, the attenuation characteristics of different frequency components are studied, and the acoustic emission source is located according to the energy of different frequency components. The results indicate that the propagation distance is the main factor affecting the attenuation of AE signals. The longer the propagation distance, the greater the degree of attenuation. The attenuation characteristics of high-frequency components of acoustic emission signals deviate from the ideal attenuation model after the propagation distance greater than 10 cm. The higher the frequency components of acoustic emission signals, the faster they attenuatewhen propagation in elm and pine specimen.

Emerging threats in Central Asia: Comparative characterization of organic and elemental carbon in ambient PM2.5 in urban cities of Kazakhstan.

This study (June 2022 - July 2023) investigates the atmospheric concentrations of carbonaceous species, including organic carbon (OC) and elemental carbon (EC), in PM2.5 in two major cities in Kazakhstan. Samples were collected from two sites in Almaty (Seifullin and KazNU) and one in Astana. The results showed that Almaty had significantly higher annual average concentrations of OC (10.8 and 10.5 μg/m3) and EC (1.68 and 1.87 μg/m3) compared to Astana (OC: 7.1 μg/m3, EC: 0.61 μg/m3). Both cities exhibited pronounced seasonal variations, with significantly elevated concentrations (1.5-3.4 times for OC, 2.1-4.8 times for EC) during the heating season (October-March) compared to the non-heating season. This indicates a significant influence of coal and biomass combustion for heating on carbonaceous aerosol concentrations. Both cities' OC/EC ratios varied widely (2.6-39.4), showing strong positive correlations (0.61-0.94) across all seasons except summer, suggesting a common primary emission source. Primary organic carbon dominated OC levels in winter (71-74%), whereas secondary organic carbon contributed significantly to OC concentrations in summer (43-50%). Higher OC-EC concentrations correlated with lower atmospheric visibility values. The OC-EC contributions to the total light extinction coefficient were estimated to be 15.3-15.9% for Almaty and 12.0% for Astana stations.

Challenges in Observation of Ultrafine Particles: Addressing Estimation Miscalculations and the Necessity of Temporal Trends.

Ultrafine particles (UFPs) pose a significant health risk, making comprehensive assessment essential. The influence of emission sources on particle concentrations is not only constrained by meteorological conditions but often intertwined with them, making it challenging to separate these effects. This study utilized valuable long-term particle number and size distribution (PNSD) data from 2018 to 2023 to develop a tree-based machine learning model enhanced with an interpretable component, incorporating temporal markers to characterize background or time series residuals. Our results demonstrated that, differing from PM2.5, which is significantly shaped by planetary boundary layer height, wind speed plays a crucial role in determining the particle number concentration (PNC), showing strong regional specificity. Furthermore, we systematically identified and analyzed anthropogenically influenced periodic trends. Notably, while Aitken mode observations are initially linked to traffic-related peaks, both Aitken and nucleation modes contribute to concentration peaks during rush hour periods on short-term impacts after deweather adjustment. Pollutant baseline concentrations are largely driven by human activities, with meteorological factors modulating their variability, and the secondary formation of UFPs is likely reflected in temporal residuals. This study provides a flexible framework for isolating meteorological effects, allowing more accurate assessment of anthropogenic impacts and targeted management strategies for UFP and PNC.

Soil pollution with heavy metals in the vicinity of coal-fired power plants in Taean and Seocheon, Chungnam Province, South Korea.

This study investigated the distributions of heavy metals (Cd, Cu, Hg, Ni, Pb, and Zn) in agricultural soils near coal-fired power plants in Taean and Seocheon, South Korea, considering wind direction and distance from the plants. Additionally, pollution assessment for these heavy metals was conducted using the geoaccumulation index (Igeo) and enrichment factor. Results showed that heavy metal concentrations in the studied soil samples were below Korean environmental criteria for agricultural soil (Cd: 4, Cu: 150, Hg: 4, Ni: 100, Pb: 200, and Zn: 300mg/kg). However, a significant proportion of samples exceeded average levels found in uncontaminated soils. Spatial distribution analysis revealed higher concentrations of Cd and Pb southwest of the Taean plant, influenced by prevailing northeast winds. In Seocheon, soils within 4km of the plant exhibited elevated levels of Cd and Ni, suggesting coal combustion as a potential contamination source. Pollution assessment indicated that Cd and Pb in soils near both thermal power plants were more enriched by artificial activity compared to agricultural soils in control areas. Sequential extraction results showed that heavy metals in soils within 4km of the Seocheon plant had higher proportions of exchangeable to organic-associated forms than soils beyond 4km, indicating a risk of high bioavailability near emission sources. This study highlights the significant impact of coal-fired power plant emissions on soil contamination, emphasizing the need for continuous monitoring and management. Environmental policies should consider wind patterns and proximity to emission sources to effectively mitigate contamination risks.

Research on Industrial CO2 Emission Intensity and Its Driving Mechanism Under China’s Dual Carbon Target

As global climate change becomes increasingly severe, industrial CO2 emissions have received increasing attention, but the impact factors and driving mechanisms of industrial CO2 emission intensity remain unclear. Based on panel data from 2010 to 2021 in Shandong Province, a key economic region in eastern China, the industrial CO2 emission intensity under China’s dual carbon target was analyzed using multivariate ordination methods. The results showed that (1) total CO2 emissions from industry are increasing annually, with an average growth rate of 3.74%, and electricity, coal, and coke are the primary sources of CO2 emissions. (2) Total CO2 emissions originated primarily from the heavy manufacturing, energy production, and high energy intensity industry categories, and the CO2 emission intensity of different types of energy increased by 21.24% from 2010 to 2021. (3) CO2 emission intensity is significantly positively correlated with the proportion of high energy intensive industry, energy consumption intensity, and investment intensity and significantly negatively correlated with gross industrial output. In addition, the effects of different types of energy on industrial CO2 emission intensity varied, and coal, coke, electricity, and diesel oil were significantly positively correlated with CO2 emission intensity. Therefore, to reduce the CO2 emission intensity of the industrial sector in the future and to achieve China’s dual carbon target, it is necessary to adjust and optimize the industrial and energy structure, strengthen technological progress and innovation, improve energy utilization efficiency, improve and implement relevant policies for industrial carbon reduction, and then ensure the sustainable development of the economy, society, and environment.

Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory.

Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving sustainable development goals (SDGs). To advance the literature on densely populated cities and highly commercialized regions, this research evaluates the total-factor carbon emission efficiency index (TCEI) of 27 cities in China's Yangtze River Delta (YRD) urban agglomeration at different stages from 2011 to 2020 using two-stage dynamic data envelopment analysis (DEA). The study carries out regression analysis and a long-short-term memory model (LSTM) to respectively filter out the factors and predict TCEI. The results indicate the following. (1) The total efficiency of 27 cities has significantly improved from 2011 to 2020, and there are obvious spatial heterogeneity characteristics. (2) In terms of stages, most cities' efficiency values in the initial stage (energy consumption) exceed those in the second stage (sustainable land utilization). (3) In terms of influencing factors, urban green space's ability to capture carbon has a notably positive correlation with carbon emission efficiency. In contrast, the substantial carbon emissions resulting from human respiration are a negative factor affecting carbon emission efficiency. (4) Over the forthcoming six years, the efficiency value of land use TCEI in the YRD urban cluster is forecasted to range between 0.65 and 0.75. Those cities with the highest performance are projected to achieve an efficiency value of 0.9480. Lastly, this research investigates the interaction between actors and land resources on TCEI, resulting in a beneficial understanding for the former to make strategic adjustments during the urbanization process.

Developments in caloric measurements, materials, and devices at Calorics 2024

Abstract Heating and cooling combined constitute the world’s largest form of end-use energy and the largest source of carbon emissions. It is therefore interesting to explore heat pumps based on caloric materials, which offer promising and environmentally friendly alternatives to gas combustion and vapor compression. The possibility of replacing these traditional methods of heating and cooling motivates the current research on caloric materials and devices. Here, we report the latest developments from the second biennial Calorics conference. Graphical abstract Highlights Caloric materials offer environmentally friendly alternatives to traditional heating and cooling technologies, addressing global energy and carbon emission challenges. The latest developments on caloric measurements, materials and devices were presented at the second biennial Calorics conference in Cambridge (UK). Discussion How can caloric technologies be made more energy efficient to ensure they outperform traditional vapor-compression systems? What are the most significant barriers to scaling caloric materials and devices from lab-scale prototypes to commercial applications? Could integrating caloric technologies with renewable energy sources, such as solar or waste heat recovery, offer sustainable solutions for heating and cooling?

Pre-Commercial Demonstration of a Photosynthetic Upgrading Plant: Investment and Operating Cost Analysis

Pig farms have been identified as one of the most important sources of greenhouse gas emissions. This study demonstrates the production of vehicle biomethane in a demonstration prototype plant based on photosynthetic upgrading technology, where the CO2 and H2S present in biogas are consumed by a microalgae culture. The information collected during the prototype construction allowed for an assessment of the capital and operating costs of this novel biogas upgrading technology with other conventional systems. With this objective, the costs of the equipment comprising the biogas cleaning and purification system were calculated considering a biogas flow rate of 5 m3 h−1, corresponding to a small–medium biogas plant and an average pig farm size. The sustainability and competitiveness of the algae upgrading system and the low capital and operating costs vis à vis other upgrading technologies were proven. With a net energy production of 687 kWh day−1 and an annual profit of 30,348 € in a 3500 head pig farm, this technology can be easily installed in livestock farms, increasing the benefits and reducing the carbon footprint.

Estimating methane emissions from the waste sector in southern ontario using atmospheric measurements

ABSTRACT We estimate methane emissions rates for urban waste treatment facilities from mobile in situ atmospheric concentration measurements using an inverse Gaussian plume methodology at facilities in Southern Ontario, Canada. We use these estimated emissions rates to investigate, update, and improve the existing high resolution methane inventories at the facility level for waste sources throughout the Greater Toronto Area and Southwestern Ontario. Our measurements encompass tens of thousands of kilometers worth of mobile survey data collected over 7 years, encompassing more than 650 downwind transects where we surveyed 14 active landfills, 11 closed landfills, 2 organic waste processing facilities, 3 open air windrow compost facilities, and 11 water resource recovery facilities across our study region. These sources account for 77% of the active landfills within Southern Ontario, which is estimated in inventories to be the largest source of methane emissions in the region. Within the Greater Toronto Area (GTA) megacity, the measured facilities represent about 52% of the total inventoried non-wetland methane emissions. We find that emissions from closed landfills are lower than inventory estimates, with significant implications for the methane budget in the GTA. We update the Facility Level and Area Methane Emissions for the GTA inventory with our measured emissions rates, which results in a 54% decline in the solid waste emissions, effecting a 35% lower estimate for the total anthropogenic methane emissions in the region. We attribute the bulk of this difference to a single facility: the Keele Valley landfill. Our atmospheric measurements also serve as a novel metric for evaluating the discrepancies between four facility level, and two high resolution gridded methane emissions inventories. Based on linear regressions of our measured emissions versus inventoried values, we find that the facility level first order decay model maintained by Environment and Climate Change Canada (ECCC) to be the most consistent with our measured emissions rates at landfills and the self-reported emissions to the Greenhouse Gas Reporting Program of ECCC to be the least consistent with our measurements.

The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands

Abstract. Ground-based remote sensing instruments have been widely used for atmospheric research, but applications for air quality monitoring remain limited. Compared to an in situ instrument that provides air quality conditions at the ground level, most remote sensing instruments (nadir viewing) are sensitive to a broad range of altitudes, often providing only integrated column observations. These column data can be more difficult to interpret and to relate to surface values and hence to “nose-height-level” health factors. This research utilized ground-based remote sensing and in situ air quality observations in Canada's Athabasca oil sands region to investigate some of their differences. Vertical column densities (VCDs) of SO2 and NO2 retrieved by Pandora spectrometers located at the Oski-Otin site at Fort McKay (Alberta, Canada) from 2013–2019 were analyzed along with measurements of SO2 and NO2 surface concentrations and meteorological data. Aerosol optical depth (AOD) observations by a CIMEL sunphotometer were compared with surface PM2.5 data. The Oski-Otin site is surrounded by several large bitumen mining operations within the Athabasca oil sands region with significant NO2 emissions from the mining fleet. Two major bitumen upgraders that are 20 km south-east of the site have total SO2 and NO2 emissions of about 40 and 20 kt yr−1, respectively. It was demonstrated that remote sensing data from Pandora and CIMEL combined with high-vertical-resolution wind profiles can provide information about pollution sources and plume characteristics. Elevated SO2 VCDs were clearly observed for times with south and south-eastern winds, particularly at 200–300 m altitude (above ground level). High NO2 VCD values were observed from other directions (e.g., north-west) with less prominent impacts from 200–300 m winds. In situ ground observations of SO2 and NO2 show a different sensitivity to wind profiles, indicating they are less sensitive to elevated plumes than remote sensing instruments. In addition to measured wind data and lidar-observed boundary layer height (BLH), modelled wind profiles and BLH from ECMWF Reanalysis v5 (ERA5) have been used to further examine the correlation between column and surface observations. The results show that the height of emission sources (e.g., emissions from high stacks or near the surface) will determine the ratio of measured column and surface concentration values (i.e., could show positive or negative correlation with BLH). This effect will have an impact on the comparison between column observations (e.g., from the satellite or ground-based remote sensing instruments) with surface in situ measurements. This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing and in situ observations in air quality monitoring and research.

Contribution of interference to the magneto-optical transverse Kerr effect in white light

Objectives. When measuring the transverse Kerr effect on thin-film structures, interference effects have a great influence on the result obtained. In conference presentations, some researchers have reported on the use of white light in experiments. In their opinion, despite the thickness of the studied layers being much less than the wavelength of light, white light can help avoid interference effects and/or resonant excitation of plasmon waves. The aim of the present work is to verify the validity of such statements using simulation.Methods. In order to solve this problem, the method of computer simulation was used. A numerical solution of equations was compiled for a model structure for various thicknesses and materials of layers.Results. The simulation results show that interference effects in different parts of the spectrum when using white light sources do not neutralize each other. The magnitude of the effect is affected not only by the thickness of the structure layers, but also by the shape of the source emission spectrum, as well as the sensitivity curve of the photodetector. In this case, the output of the measured value of the effect to a plateau at relatively large thicknesses of the magnetooptical film is due to the light being absorbed in the thickness of the magneto-optical film and is negligibility of the back reflection of light from the substrate.Conclusions. The presented technique takes into account the influence of interference effects when measuring the equatorial Kerr effect in white light or using other sources having a wide spectral range, thus improving the interpretation of experimental results. The results are relevant to the development and research of the physical foundations for creating new and improving existing devices in micro-, nano-, and solid-state electronics, as well as quantum devices, including optoelectronic devices and converters of physical quantities.

Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions

After stabilizing in the mid-2000s, atmospheric methane (CH4) levels have accelerated over the past decade. In response, satellite-based inversion techniques have been employed to meet the increasing demands of the climate community. In this study, the Integrated Methane Inversion (IMI) model, a novel approach based on the TROPOspheric Monitoring Instrument (TROPOMI), is used to quantify CH4 emissions across Denmark. Over 900,000 TROPOMI observations from spring to early autumn of 2018–2022 were used to inform the inversions. Overall, TROPOMI CH4 concentrations within the inversion domain showed an upward trend of approximately 12.71 ppb per year, reflecting the global trend. Excluding 2022, which included only four months of data, the inversions suggest an underestimation of emissions by 190(160–215) × 103 tonnes, or 66(56–75)% of prior estimates. Northern and southern Jutland, along with the Copenhagen metropolitan area, were identified as key sources of CH4 emissions. Additionally, the inversions indicated a decline in emissions during the COVID-19 pandemic, despite stable activity data. This study demonstrates the feasibility of using the IMI model to monitor CH4 emissions in small countries like Denmark, offering a satellite-based perspective to better identify and mitigate these emissions.

Quantifying and Mitigating Greenhouse Gas Emissions in Egg-Laying Hen Farming: A Path Towards Carbon Neutrality

This study presents a comprehensive framework for assessing and mitigating greenhouse gas (GHG) emissions in commercial egg-laying hen farming in Uttaradit Province, with the aim of achieving carbon neutrality within the poultry sector. Employing a detailed life cycle assessment (LCA) over a 450-day production period, this research identifies key sources of emissions, with feed consumption identified as the largest contributor, followed by water use and energy demands. To address these emissions, the study explores several innovative strategies: transitioning to solar photovoltaic systems for lighting and water pumping, shifting from diesel to biodiesel for fuel, and optimizing feed compositions. Additionally, advanced manure management practices are proposed to reduce methane and nitrous oxide emissions. Collectively, these interventions could significantly diminish the emissions associated with hen farming operations, thereby advancing environmental sustainability. This work not only provides actionable insights for poultry farms seeking to lower their emissions but also offers a scalable and adaptable model with broader implications for sustainable practices across the agricultural sector. The findings underscore the importance of renewable energy integration, feed optimization, and efficient waste management in mitigating the environmental impact of agriculture, thereby informing both policy and practice in the pursuit of carbon-neutral food production.

Characterizing and sourcing metal air contamination coupling concentrations and lead isotopes from moss biomonitoring in urban cemeteries

Populations are constantly exposed to airborne metals, in particular in urban areas. Despite their proven links to health issues, their origin and fate are still subject to debate. Bioindicators, by taking up and cumulating atmospheric metals over time, have been widely used to proxy environmental quality over large areas, at various time scales. Using the example of the Paris region, we investigated the potential for the Grimmia pulvinata moss species to both characterize air metal contamination and to identify its main sources. To this end, we coupled metal/metalloid (Al, As, Cd, Cr, Cu, Fe, Ni, Pb, Sb, Sr, V and Zn) concentrations and Pb isotope ratios from samples collected in cemeteries in the city and its suburbs. Metal enrichment factors ranged between 2 and 10 for As, Cr, Fe, Ni, Sr, V, between 50 and 100 for Cu, Pb and Zn and > 100 for Cd and Sb, indicating a dominant anthropogenic origin. Principal component analysis showed that 3 principal components explained 89% of the metal variations: (i) European atmospheric background, (ii) regional urban sources, and (iii) resuspension of regional soils. This was corroborated by Pb isotope ratios, whose variations were modelled by a ternary mixing that considered the same 3 emission sources. Using a MixSIAR isotope model, we reveal that the European atmospheric background contributes slightly (< ~ 5%) and that within 20 km of the city center bioindicators are mostly impacted by urban sources (contributions: 50–80%). Samples collected > 20 km show almost equal contributions of the endmembers representing urban activities and agricultural soil resuspension.

Provenance of fine-grained Quaternary sediments in the Tengger Sandy Desert recorded by Sr-Nd isotopes and its linkage with Quaternary aeolian silts on the Chinese Loess Plateau

Aeolian dust, a product of aridification, can directly affect the climate system by reflecting and absorbing solar radiation, or indirectly by altering cloud properties. It also plays a role in regulating carbon uptake in marine ecosystems through the iron fertilization effect. The Gobi Deserts in southern Mongolia have traditionally been considered major sources of sandstorms and dust emissions in Asia's interior. However, a recent sediment tracing study using U-Pb age spectra of coarse detrital zircon grains challenges the role of these sandy deserts as sources of aeolian dust for the downwind Chinese Loess Plateau (CLP). This study aimed to identify the provenance area of Quaternary fine-grained sediments in the proximal sandy Desert Tengger and to explore their potential link with aeolian dust in the downwind CLP during the Quaternary. (1) 87Sr/86Sr values ranging from 0.715124 to 0.728164 and 143Nd/144Nd values from 0.511987 to 0.512192 were measured in the acetic acid-insoluble <75 μm fraction of 30 Quaternary sediment samples from the core BJ14, drilled in the Tengger Sandy Desert hinterland. (2) These 143Nd/144Nd values resemble those of riverine sediments eroded from rocks in the Northern Qinghai-Tibet Plateau (NTP) but differ from those eroded from the Gobi Altai Mountains (GAMs). This indicates that the NTP is the primary source of the <75 μm component of the Tengger Sandy Desert sediments during the Quaternary. Alongside previous studies on U-Pb age spectra of detrital zircons, our results suggest that after 0.8 Ma, the contribution of fine-grained detritus from the NTP decreased, although it continued to dominate the provenance of fine-grained sediments. However, the contribution of coarse detritus from the NTP increased significantly, becoming predominant in coarse grains, especially after 0.36 Ma. These changes record enhanced physical weathering and wind transporting capacity driven by temperature differences in the context of global aridification following the Kunlun-Huanghe Movement and the Mid-Pleistocene Transition. (3) After 0.9 Ma, a deviation on 143Nd/144Nd values of the <75 μm Quaternary sediments within the hinterland of Tengger from that of the 28–45 μm fraction in the loess/paleosol sequence in Lingtai in the central CLP suggests that the source-sink linkage between the hinterland Tengger and Chinese Loess Plateau was weak after 0.9 Ma. But high shoreline areas of the paleolake Tengger might be a persistent source area emitting fine-grained detritus to the CLP throughout the Quaternary period. This study indicates further research is needed to enhance our understanding of dust fluxes in northern China.

Sixty-year trends in sulphur dioxide emissions from anthropogenic ground-based sources in Antarctica

Abstract Knowledge of trends of pollutants released into the environment is very important for interpreting the observed trends in pollution of natural environments and forecasting their development. This article reconstructs for the first time a series of sulphur dioxide emissions from the main categories of land-based sources of emissions in Antarctica (diesel generators, heating systems, vehicles and waste incineration) over 60 years: from the beginning of the intensive construction of scientific stations in 1960 until 2019. The trends in the sulphur content of fuels and the dynamics of fuel consumption by the main categories of emission sources are taken into account. According to the estimates obtained, total emissions of sulphur dioxide in Antarctica varied in the range of 28.6–161.3 tons. This paper establishes that the greatest levels of sulphur dioxide emissions occurred in the late 1980s–beginning of the 1990s. In subsequent years, there was a rapid reduction in emissions, primarily due to a reduction of the sulphur content of fuels. The rates of reduction of sulphur dioxide emissions for different areas of Antarctica are also shown.