Contribution Of Different Sources Research Articles

Source Apportionment of Morphine in Wastewater

It is a new approach to identify legal or illegal use of morphine through information on municipal wastewater. However, the sources of morphine in wastewater are complex, and distinguishing the contribution of different sources has become a key issue. A total of 262 influent samples from 61 representative wastewater treatment plants in a typical city were collected from October 2022 to March 2023. The concentrations of morphine, codeine, thebaine, papaverine, noscapine, and monoacetylmorphine were analyzed in wastewater and poppy straws. Combined with the proportion of alkaloids in poppy straws, the source analysis of alkaloids in wastewater was analyzed using the ratio method and positive matrix factorization model (PMF). Only five alkaloids were detected in wastewater, and monoacetylmorphine, a metabolite of heroin, was not detected. The concentrations of morphine and codeine were significantly higher than those of noscapine, papaverine, and thebaine. By constructing the ratios of codeine/(morphine + codeine) and noscapine/(noscapine + codeine), the source of poppy straw could be qualitatively distinguished. The PMF results showed that three sources of morphine for medical use, poppy straw, and codeine contributed 44.9%, 43.7%, and 9.4%, respectively. The different sources varied in these months due to the COVID-19 and influenza A outbreaks, in which the use of drugs containing poppy straws and codeine was the main source, whereas the use of morphine analgesics remained relatively stable. Inventory analysis further demonstrated the reliability of the source contributions from the PMF model, and morphine was not abused in this city.

Development of a multi-level factorial data assimilation approach for groundwater contaminant sources identification

The ensemble Kalman filter (EnKF) is recognized as a widely used approach for groundwater contamination sources (GCSs) parameters identification. The identification accuracy is affected by the quantification of sources of uncertainty (such as random disturbances on model inputs and measurements) in the assimilation process, but few studies have revealed the contributions of different sources of uncertainty on identification accuracy. To this end, this study developed an innovative multi-level factorial data assimilation (MFDA) approach, which integrates ensemble Kalman filtering and multi-level factorial analysis, to comprehensively reveal the impact of sources of uncertainty on the GCSs parameters identification accuracy for the first time. Not only did it explore the direct impact of individual sources of uncertainty on the GCSs parameters identification accuracy, more importantly, it also revealed the composite ones from multi-parameter interactions among these sources of uncertainty. The developed MFDA approach quantified the contributions of multiple sources of uncertainty, including model input data error (i.e. precipitation), model parameter error (i.e. hydraulic conductivity), contaminant concentration measurements error, and ensemble size. And the feasibility of the developed approach was verified by two hypothetical numerical case studies. The results indicated that: i) it was critically important to reduce the contamination concentration measurement errors to improve GCSs parameter identification accuracy. ii) model parameter and model input data were not sensitive to the identification accuracy. iii) the interaction between sources of uncertainty significantly affects the identification accuracy, which illustrated the interaction cannot be ignored in the identification process. Overall, this study highlights that the developed MFDA approach represents a promising solution for improving GCSs parameters identification accuracy.

Application of VIC-WUR model for assessing the spatiotemporal distribution of water availability in anthropogenically-impacted basins

Climate change, rapid increase in population, and urbanization have given rise to over-exploitation and shortage of freshwater resources. Acquiring accurate representations of fresh water availability is therefore crucial to sustainable development. Based on the underlying hydrological processes and storage types, fresh water can be divided into blue and green water components. Hence, quantification of the spatio-temporal distribution of blue and green water requires estimating the components of terrestrial water cycle. In this study, a framework is proposed to evaluate the water scarcity using the blue and green water concept. In this framework, the Wageningen Institute and Research (WUR) version of the Variable Infiltration Capacity Model (VIC) is employed to simulate terrestrial water cycle. Compared to VIC model, VIC-WUR model employs additional modules to account for sectoral water demands, return flows, and groundwater withdrawals, however, very limited number of its applications have been reported so far. The Divandareh-Bijar (DBJ) basin in west of Iran is selected because it has experienced severe anthropogenic alterations in the past three decades. To address precipitation and parameter uncertainty, the VIC-WUR model is separately calibrated for three precipitation datasets. As a part of this framework, the calibrated model is used to simulate blue and green water components and their corresponding scarcity metrics for the first time. According to the results, blue and green water resources in the DBJ are relatively scarce. The results also highlight the importance of considering anthropogenic impacts on the spatiotemporal dynamics of green and blue water resources. Additionally, quantification of the uncertainty in blue and green water components can help produce more reliable estimations for intelligent management of water resources. The ANalysis Of VAriance (ANOVA) method is therefore used to quantify the contribution of three major factors, including precipitation inputs, model parameters, and the interaction of these two, on the uncertainty of calculated water scarcity metrics. Structural uncertainty is implicitly addressed through the use of the modified version of the VIC model. The results indicate seasonality of these contributions for the two metrics under investigation and the differences in relative contribution of different sources to the overall uncertainty. The proposed framework could be employed to identify water stress in various spatiotemporal scales across the globe.

Who matters and why? The contributions of different sources of social support to doctoral students' academic engagement

AbstractSocial support is a crucial factor in the academic engagement of doctoral students, which is vital to their overall success. While past studies have mostly focused on the support from doctoral supervisors, support from other significant groups, including institutions, peers and families, has been largely neglected, and even no study has investigated their contributions to doctoral students' development. Drawing from the job demands‐resources model, this study investigated the contributions of different sources (institutions, supervisors, peers and families) of social support to doctoral students' academic engagement. It further examined the mediating role of grit within these relationships. A sample of 472 doctoral students across various disciplines from 10 universities in mainland China responded to an online survey. Results showed that institutional support and supervisory support positively predicted doctoral students' academic engagement, while peer support and family support did not significantly predict academic engagement. Furthermore, grit was found to mediate the relationship between support from institutions and supervisors and academic engagement. Practical implications for higher education institutions, doctoral supervisors and programs are discussed.

Job function as determinant of clinker exposure at workplaces during cement production.

In the cement production industry, exposure to airborne particulate matter is associated with a decline in lung function and increased airway symptoms. Exposure to clinker-the major constituent of cement and supposedly the cause of the observed adverse health effects-was determined recently in 15 cement production plants located in 8 different countries (Estonia, Greece, Italy, Norway, Sweden, Switzerland, Spain, Turkey). It was shown that the median clinker abundance in the thoracic fraction varied between approximately 20% and 70% for individual plants. The present study complements the previous work by investigating the significance of job function as a determinant of clinker exposure. The elemental composition (water and acid-soluble fractions separately) of 1,227 personal thoracic workplace samples was analyzed by positive matrix factorization (PMF) to determine the contribution of different sources to the composition of airborne particulate matter and to quantify the clinker content. Median thoracic mass air concentrations varied for individual job functions between 0.094 and 12mg/m3 (estimated separately for different plants). The PMF 5-factor solution yielded median relative clinker abundances in the personal thoracic samples between 7.6% and 81% for individual job functions. Thoracic clinker air concentrations are highest for cleaning, production, and maintenance work, and lowest for administration and other work. Foremen and laboratory personnel show intermediate exposure levels. The plant was found to have a much higher contribution to the total variance of the thoracic clinker air concentrations than the job function. Thoracic clinker air concentrations (medians between 0.01 and 5.5mg/m3) are strongly correlated with the thoracic mass air concentrations and to a lesser extent with the relative clinker abundance in an aerosol sample. Job function is an important predictor of exposure to clinker in the cement production industry. As clinker is suspected to be the causal agent for the observed adverse health effects among cement production workers, the clinker air concentration may be a better exposure metric than thoracic air mass concentration despite the strong correlation between the two. Reduction strategies should focus on the most exposed job categories cleaning, production, and maintenance work.

Hydrochemical Characteristics and Control Factors of Shallow Groundwater in Anqing Section of the Yangtze River Basin

Shallow groundwater is the main source of water for living and industrial and agricultural production in Anqing City, which is an important basic guarantee to maintain the sustainable development of the social economy and regional ecological environment. In order to further study the water chemical characteristics and controlling factors of shallow groundwater in Anqing City, 196 groups of shallow groundwater samples were collected. A Piper diagram graph, Gibbs chart, ion ratio, and mathematical statistics were comprehensively used to study the water chemical characteristics and controlling factors of groundwater in Anqing City, and the contribution of different sources to the water chemical components of groundwater was quantitatively evaluated. The results showed that the shallow groundwater in Anqing City was weakly alkaline, with pH values ranging from 5.84 to 8.38, with an average value of 7.21. The TDS ranged from 47 to 1 620 mg·L-1, with an average of 324.21 mg·L-1. HCO3- and Ca2+ were the main anions, and the water chemical type was HCO3-Ca type. The chemical components of groundwater were affected by rock weathering leaching, cation alternating adsorption, mineral dissolution and precipitation, and human activities. Ca2+, Mg2+, and HCO3- were mainly derived from the weathering dissolution of carbonate and silicate; Na+, Cl-, and SO42- were affected by industrial activities and domestic sewage discharge; and K+ and NO3- were affected by agricultural activities. The APCS-MLR receptor model analysis further revealed that the chemical components of groundwater were mainly geological factors, industrial factors, agricultural factors, and unknown sources, and their contribution rates were 45.35%, 14.19%, 25.38%, and 15.08%, respectively. Geological factors were important sources of hydrochemical components of shallow groundwater, and human activities aggravated the evolution of groundwater hydrochemistry.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Air pollution biomonitoring in an urban-industrial setting (Taranto, Italy) using Mediterranean plant species

This study presents the first report on the elemental composition of five Mediterranean plant species (Pinus pinaster, Eucalyptus camaldulensis, Nerium oleander, Olea europaea and Pittosporum heterophyllum) to trace industrial emissions in Taranto, Italy, a mixed-use industrial and urban setting. Potential metal sources include vehicular traffic, steel and cement plants, and a petrochemical refinery. Samples were collected from 29 sites covering the Tamburi-Lido Azzurro neighbourhood and the historical quarter Città Vecchia-Borgo. High concentrations of toxic metals were observed in all samples, with marked inter-species variability. Model based clustering identified two distinct groups, one dominated by pine needles with higher metal concentrations than the other group composed of the other four plant species. The contamination factor (CF) and pollution load index (PLI) indices which use background samples to standardise the level of pollution, were used to remove species effect allowing for direct site comparison. Spatial analysis of CF and PLI data identified pollution hotspots near industrial areas and major roads, with areas of little to no air pollution near green spaces. Statistical analysis of the CFs revealed the contribution of different sources to element emissions. Ni and Cr were primarily emitted from the steel plant and petrochemical refinery, while Fe and Al were associated with road traffic emissions, and geogenic elements Ca, Mg, K, and Na were linked to marine spray and Saharan dust. This study demonstrates that combining multiple plant species with pollution indices can be a cost-effective biomonitoring approach for assessing air pollution and creating a high-density spatial monitoring network.

Air pollutant emissions and sources in Lao People’s Democratic Republic: a provincial scale analysis for years 2013-2019

Recent rapid economic development in Lao People’s Democratic Republic (PDR) has increased national fuel consumption, vehicle fleet, industrial output, waste generation, and agricultural production. This has contributed to national average ambient fine particulate matter (PM2.5) air pollutant levels that are four times higher than World Health Organisation guidelines. Emission inventories are a key tool in understanding the major sources to these air pollution levels, and provide a starting point to identify where mitigation action can be targeted. A national air pollutant emission inventory has not been developed in Lao PDR and, combined with a limited air quality monitoring network means there is limited capacity to develop and track the effectiveness of mitigation actions. This study describes the first air pollutant emission inventory at the national and provincial scale for Lao PDR, covering 2013–2019. Emissions of nine air pollutants, and two greenhouse gases, were quantified using national statistics and international default emission factors. In 2019, national total PM2.5, Nitrogen Oxides (NOx), Black Carbon (BC), Sulphur Dioxide (SO2), Non-Methane Volatile Organic Carbons (NMVOCs), and Ammonia (NH3) were 125, 83, 9.7, 26, 219, and 99 thousand tonnes respectively. Key source sectors include forest fires, residential cooking, agriculture, electricity generation, and transport. However, the contribution of different sources varies across provinces. Forest fires are the primary source determining the spatial trend of particulate air pollution while residential and agricultural emissions contribute more significantly to rural provinces such as Savannakhet. Key sectors in major urban provinces (Vientiane Capital and Xayaboury) are industry, transport and electricity generation. These sectors are also significant sources of greenhouse gases (CO2 and CH4), demonstrating the potential for identification, evaluation and prioritisation of actions that simultaneously improve air quality and achieve Lao PDR’s international climate change commitments.

Implementation of an On-Line Reactive Source Apportionment (ORSA) Algorithm in the FARM Chemical-Transport Model and Application over Multiple Domains in Italy

A source apportionment scheme based on gas and aerosol phase reactive tracers has been implemented in the chemical-transport model FARM, to efficiently estimate contributions of different sources to ambient concentrations. The on-line scheme deals with all the main processes that the chemical species undergo in the model, to enhance consistency with the calculation of bulk concentrations. The fate of precursors through gas-phase chemical reactions is followed by an efficient solver that determines their incremental reactivity, while the contributions to the secondary particulate species from their gaseous precursors is determined by assuming the thermodynamic equilibrium between the two phases. The paper details the new employed methodologies and illustrates the application of the apportionment scheme (based on 6 source sectors) to PM10 and O3, simulated on three domains of different dimensions in Italy, all sharing the same horizontal resolution and a common region (Lombardy). Spatial patterns of results show, on average, a relevant contribution of heating on PM10 concentration in January, with local hotspots dominated by road traffic. Contributions appear consistent in the three simulated domains, apart from the boundary conditions, influenced by the dimension of the domain. Hourly series of contributions to O3 concentrations in July at three selected sites show the dominance of boundary conditions, underlining the large scale of O3 formation. Finally, for PM10 components, the resulting sectorial contributions are compared with the impacts computed via the brute force method, showing that results are similar for elemental carbon and sulfate, while they are different for nitrate and ammonium, due to a different allocation of contributions and impacts between the methods. Each approach responds in principle to a different purpose, and their combined use provides possibly a wide set of information useful for addressing the different air quality management needs.

Identification of Causes of Air Pollution in a Specific Industrial Part of the Czech City of Ostrava in Central Europe

This contribution deals with the assessment of air pollution caused by atmospheric aerosol particulate matter fraction PM10 and benzo[a]pyrene (BaP) in the urban agglomeration of Ostrava, located in the Czech Republic in Central Europe. The motivation for this research was the need to identify the sources of air pollution in the area, particularly in locations where the contribution of different sources to concentrations of pollutants of concern has not been elucidated yet. In this study, source apportionment in the vicinity of the industrial hot spot was performed by statistically evaluating measured pollutant concentrations as a function of meteorological variables and using the Positive Matrix Factorization (PMF) receptor model. A significant methodological innovation and improvement over previous assessments was the higher monitoring resolution of benzo[a]pyrene, with samples collected at three-hour intervals instead of the standard 24 h collection period. The key findings indicate that in the cold part of the year, secondary particles—specifically sulfates and ammonium nitrates—were responsible for the most significant portion of PM10 air pollution throughout the area of interest. The contribution of these particles ranged from one-third to two-fifths of the total concentration, except at the industrial site of Ostrava–Radvanice (TORE), where they accounted for approximately one-fifth of the measured pollution concentration level. Emissions from individual household heating were identified as the main source of this type of pollution. With regards to benzo[a]pyrene air pollution, this study found that in the whole area of interest, except for the Ostrava–Radvanice site, it mainly originated from individual heating with coal (90%). In contrast, at the Ostrava–Radvanice site, two-thirds of the benzo[a]pyrene pollution came from the premises of Liberty Ostrava a.s., primarily from coke production, and less than one-third came from local domestic heating. This study also determined the spatial extent of the occurrence of extremely high benzo[a]pyrene concentrations (above 5 ng/m3), which are estimated to affect nearly 10,000 inhabitants. The results confirm that the data from the TORE station are only representative of its immediate surroundings and are not applicable to the assessment of air quality and causes of air pollution in the whole city of Ostrava or the urban area of Ostrava–Radvanice as a whole. After years of research, these findings provide the Ministry of the Environment of the Czech Republic and the government with an accurate basis for implementing measures to address the identified pollution sources in the area of interest. The success of this study was made possible by the adoption of a more detailed sampling approach, which involved a resolution of 3 h instead of 24 h. This methodological improvement is a significant finding and will be useful for future source apportionment studies.

Significant contribution of different sources of particulate organic matter to the photoaging of microplastics

Particulate organic matter (POM), as an important component of organic matter, can act as a redox mediator and thus intervene in the environmental behavior of microplastics (MPs). However, quantitative information on the role of POM in the photoaging of MPs under ultraviolet (UV) light is still lacking. To raise the knowledge gap, through environmental simulation experiments and qualitative/quantitative experiments of active substances, we found that POM from peat soil has stronger oxidation capacity than POM from sediment, and the involvement of POM at high water content makes the aging of MPs more obvious. This is because the persistent radicals and electron-absorbing groups on the surface of POM indirectly generate reactive oxygen species (ROS) by promoting electron transfer, and the dissolved organic matter (DOM) released from POM under UV light (POM-DOM) is further excited to generate triplet-state photochemistry of DOM (3DOM*) to promote the aging of MPs. Theoretical calculations revealed that the benzene ring, mainly C = C, and C = O in the main chain in the plastic macromolecule structure are more susceptible to ROS attack, and the differences in the vulnerable sites contained in different plastic structures as well as the differences in the energy band gaps lead to differences in their aging processes. This study firstly elucidates the key role and intrinsic mechanism of POM in the photoaging of MPs, providing a theoretical basis for a comprehensive assessment of the effect of POM on MPs in the environment.

Temporal variability in irrigated land and climate influences on salinity loading across the Upper Colorado River Basin, 1986-2017

Freshwater salinization is a growing global concern impacting human and ecosystem needs with impacts to water availability for human and ecological uses. In the Upper Colorado River Basin (UCRB), dissolved solids in streams compound ongoing water supply challenges to further limit water availability and cause economic damages. Much effort has been dedicated to understanding dissolved solid sources, transport, and management in the region, yet temporal variability in loading from key sources such as irrigated lands and the influence of climate on dissolved solids loading remains unknown. Quantifying the contributions and temporal variability of dissolved solids loads from irrigated lands may benefit salinity management efforts. This study applies a time-varying (dynamic) modeling approach to predict annual dissolved solids loads across the UCRB from 1986 through 2017. Between 66% and 82% of the total accumulated dissolved solids load in the basin is from groundwater (storage and baseflow). Our findings link climate, irrigation, and groundwater, and confirm large storage contributions that have declined slightly with time. Dissolved solids loads increase during wet periods and decrease during dry periods, although the relative contributions of different sources vary little with time. Irrigation enhances loading efficiency relative to unirrigated areas through runoff and groundwater, and can locally be a major source of dissolved solids where irrigation occurs. Results indicate that loads from irrigated areas increase when irrigated area and/or water available for runoff increase. Increased regional aridification over the study period may have contributed to decreasing stream salinity through both quicker surface runoff and lagged groundwater storage processes. Study results may be relevant to salinity management in arid environments where water availability is limited and where irrigation influences salinity loading to streams.

Niche width and overlap of benthic invertebrates in surf zones increase with distance from the estuarine source of organic matter

Benthic invertebrates in the surf zone of exposed sandy beaches represent important links for energy circulation between benthic and pelagic food webs. This work assesses the trophic ecology of co-occurring epi- and hyper-benthic invertebrates inhabiting the surf zone of sandy beaches located close to an estuarine mouth. It illustrates that different sources of organic matter induce changes in resource utilization. The trophic positions, and the niche width and overlap of species were described using δ13C and δ15N stable isotope analysis. The contribution of different sources to the particulate organic matter was quantified through stable isotopes analysis and fatty acids profiles. Shifts in the trophic niches of dominant species reflected a decrease in the contribution of estuarine carbon to the diets along the coast. This change in contribution of estuarine carbon also influenced trophic niche properties: more diverse resources availability resulted in narrower niches without overlap while less diverse resources resulted in broad isotopic niches and a highest overlap. Results show that spatial variations in the availability of resources can modify carbon pathways and trophic interactions in coastal food webs. Whenever resources are abundant, species display a more specialized diet while food scarcity leads to broader diets, a pattern consistent with the optimal foraging theory. This resource maximization behavior commonly observed in nature is also occurring in surf zone ecosystems.

Geogas-Carried Metal Prospecting for Concealed Ore Deposits: A Review of Case Studies in China

Geogas-carried metal prospecting, an integral part of deep-penetrating geochemistry, is potentially effective in the geochemical exploration of concealed ore deposits. However, its principles and applicability remain controversial. This study summarizes and discusses the progress in geogas-carried metal prospecting in China. The method comprises three constituents: geogas, nanoparticles, and their vertical transportation. Researchers have failed to determine the exact contributions of different sources of geogas. Studies on Pb isotopes, rare earth element patterns of geogas, the comparisons between metals in soil, geogas, and ore geochemistry, and characteristics of nanoscale metals in earthgas (NAMEG), confirmed the relationship between NAMEG and concealed ore deposits. A statistical analysis of field experiments and applications showed that geogas-carried metal prospecting is applicable for the geochemical exploration of magmatic and hydrothermal Cu, Au, Zn, Pb, U, Sn, and Ag deposits and is suitable for most geochemical landscapes except deserts and cold swamps. Finally, genetic models of NAMEG anomalies were constructed. High-permeability migration channels are critical in the formation of NAMEG anomalies over concealed ore deposits. Future work entails applying geogas-carried metal prospecting to certain types of ore deposits and geochemical landscapes and studying NAMEG to provide quantitative information for targeting concealed ore deposits.

Important Role of Overland Flows and Tile Field Pathways in Nutrient Transport.

Nitrogen and phosphorus pollution is of great concern to aquatic life and human well-being. While most of these nutrients are applied to the landscape, little is known about the complex interplay among nutrient applications, transport attenuation processes, and coastal loads. Here, we enhance and apply the Spatially Explicit Nutrient Source Estimate and Flux model (SENSEflux) to simulate the total annual nitrogen and phosphorus loads from the US Great Lakes Basin to the coastline, identify nutrient delivery hotspots, and estimate the relative contributions of different sources and pathways at a high resolution (120 m). In addition to in-stream uptake, the main novelty of this model is that SENSEflux explicitly describes nutrient attenuation through four distinct pathways that are seldom described jointly in other models: runoff from tile-drained agricultural fields, overland runoff, groundwater flow, and septic plumes within groundwater. Our analysis shows that agricultural sources are dominant for both total nitrogen (TN) (58%) and total phosphorus (TP) (46%) deliveries to the Great Lakes. In addition, this study reveals that the surface pathways (sum of overland flow and tile field drainage) dominate nutrient delivery, transporting 66% of the TN and 76% of the TP loads to the US Great Lakes coastline. Importantly, this study provides the first basin-wide estimates of both nonseptic groundwater (TN: 26%; TP: 5%) and septic-plume groundwater (TN: 4%; TP: 2%) deliveries of nutrients to the lakes. This work provides valuable information for environmental managers to target efforts to reduce nutrient loads to the Great Lakes, which could be transferred to other regions worldwide that are facing similar nutrient management challenges.

Source-specific probabilistic contamination risk and health risk assessment of soil heavy metals in a typical ancient mining area

Heavy metal pollution (HMP) from mining operations severely threatens soil ecosystems and human health. Identifying the sources of soil heavy metals (HMs) and assessing source-specific risks are critical for developing effective risk mitigation strategies. In this study, a combination of methodologies including PMF, Monte Carlo analysis, soil pollution risk index, and a human health risk assessment model were utilized to investigate soil HM risks in a typical ancient mining area in Daye City, China, considering both environmental pollution and human health impacts. Cu emerged as the most significant soil pollution risk, whereas As posing the highest health risk. About 48.44 % of the multi-element integrated soil pollution risk has escalated to the heavy level. Furthermore, around 22.42 % of the non-carcinogenic risk (NCR) and 9.53 % of the carcinogenic risk (CR) exceeded unacceptable thresholds (THI > 1 for NCR and TCR > 1E-4 for CR). The PMF model identified four distinct sources: the smelting industry, traffic emissions, a combination of agricultural and natural factors, and mining activities. The mixed agricultural and natural source significantly impacted health risks, contributing 42.17 % to NCR and 53.88 % to CR, followed by the mining source, contributing 31.67 % to NCR and 24.07 % to CR. Interestingly, the mining source contributed the highest soil pollution risk at 42.45 %, while the mixed agricultural and natural source exhibited the lowest at 16.33 %. Furthermore, the study explored source-specific risk components by evaluating the contributions of different sources to specific elements. The mining source was identified as the focus for soil HMP control, followed by the mixed agricultural and natural source. Overall, this study provided an in-depth analysis of soil heavy metal risks in mining areas from the source apportionment perspective, which broadened the research framework of soil heavy metal source analysis and risk assessment, potentially providing scientific guidance for managing regional soil HMP.

Isotopic comparison of ammonium between two summertime field campaigns in 2013 and 2021 at a background site of North China

Ammonia (NH3) is the primary atmospheric alkaline gas, playing a crucial role in the atmospheric chemistry. Recently, non-agricultural emissions have been identified as the dominant sources of NH3 in urban areas. However, few studies have quantified the contributions of different sources to regional NH3. This study conducted two summertime field observations in 2013 and 2021 at a background site of North China to comprehensively explore the regional variations in concentration, nitrogen isotope composition (δ15N), and sources of ammonium (NH4+). The results indicate that NHx (NHx = NH3 + NH4+) concentration has increased in 2021, but the fNH4+ (NH4+/ NHx) has decreased significantly. The δ15N-NH4+ values show a significant increase, ranging from −4.7 ± 8.1 ‰ to +12.0 ± 2.4 ‰. The increase can be attributed to two primary factors: changes in fNH4+ resulting from the reduction of atmospheric acid gases and alterations in the sources of NH3. Bayesian simulation analysis reveals substantial variations in NH3 sources between 2013 and 2021 observations. Non-agricultural sources have significantly increased their contribution to NHx concentration, with vehicle exhaust and NH3 slip experiencing growth rates of 187 % and 104 %, respectively. Our results confirm the dominate contribution of non-agricultural sources to regional NH3 at the present stage and propose relevant mitigation strategies, which would provide essential insights for reducing NH3 emissions in North China.

Greenhouse gas emissions of Delhi, India: A trend analysis of sources and sinks for 2017–2021

Delhi is the world's second most populated city and India's capital. The objective of this study is to develop a comprehensive emission inventory of GHGs, including CO2, N2O, and CH4, and present a source apportionment of GHGs, thus setting a benchmark for developing source-specific mitigation strategies at a localized level. The study employs 2006 IPCC and Good Practice Guidelines to analyze and quantify emissions from various sources. An annual emission load of 51,081 ktCO2e for Delhi from 2017 to 2021 is estimated with an uncertainty of approximately 4%. 34,344 ktCO2e (61%) is accounted for by the stationary combustion sector. The mobile combustion sector accounts for 33% of the total emissions at 18,574 ktCO2e. The waste sector accounts for 5.2% of total emissions, followed by a meagre 0.8% contribution from the agriculture sector. It further evaluates the role of carbon stock in reducing the net emissions generated by the city. This study contributes to future policies by corroborating the findings of a GHG inventory of Delhi from 2017 to 2021 and noting significant variations in the trends in terms of the contribution of different sources to net emissions. It further reinforces the need to develop more localized inventories to target the primary emitting sectors in different regions through focused mitigation strategies.

Distribution, sources and influencing factors of organic carbon in the surface sediments of the coastal tidal flats in Jiangsu Province

Coastal tidal flats are situated in the interaction zone between the ocean and land and are vulnerable to natural changes, human activities, and global changes; these areas serve as an important mixing zone and burial area for carbon and nitrogen storage. Coastal tidal flats contribute significantly to the global carbon cycle due to their high biological productivity, high sedimentation rate, and low decomposition rate. However, there is a lack of research on the sources and influencing factors of organic carbon in surface sediments in the coastal tidal flat area of Jiangsu Province. In this study, fourteen surface sediment samples were collected from the Jiangsu coastal tidal flats, and the distribution of organic carbon was analyzed. The sources and influencing factors of sediment organic carbon were also investigated by analyzing the contents, ratios and stable isotopes of carbon and nitrogen in the sediments. The results indicated that the total organic carbon (TOC) and total nitrogen (TN) contents in the surface sediments of Jiangsu coastal tidal flats ranged from 0.09% to 0.82% and from 0.01% to 0.1%, with mean values of 0.36% and 0.04%, respectively, and that there was a significant positive correlation between TOC and TN. Moreover, the high-value areas were located mostly along the borders or in sections covered in vegetation, whereas the mudflat areas without vegetation had lower values. Considering the status of the Jiangsu coastal zone, the abandoned Yellow River estuary, Yangtze River inlet, marine benthic microalgae, C3 plants and C4 plants were selected as end members of organic carbon concentrations. The contributions of different sources were quantified using a Bayesian mixture model (MixSIAR). Among them, the abandoned Yellow River estuary and Yangtze River inlet contributed 28.1% and 19.3%, respectively, followed by marine benthic microalgae with a contribution of 26%, whereas C3 and C4 plants made limited contributions of 9% and 8.8%, respectively. Additionally, the sediment particle size, hydrodynamics, and tidal flat vegetation such as Spartina alterniflora were the key factors influencing the organic carbon distribution. In general, this study contributes to a better understanding of the biogeochemical processes and sources of organic carbon in coastal tidal flats. It also provides a solid foundation for the creation of carbon sink measures in nearshore tidal flats.