Traffic Sources Research Articles

Effects of particle-bound polycyclic aromatic hydrocarbons and plasticisers from different traffic sources on the human alveolar epithelial cell line A549

Road traffic represents a major source of particulate matter (PM), which is considered the most harmful pollutant for humans. This work aimed to evaluate the toxic effects of polycyclic aromatic hydrocarbons (PAHs) and plasticisers extracted from PM emitted by traffic, including exhaust samples, samples collected in a road tunnel and simultaneously in a nearby urban background atmosphere, and samples from the wear of distinct types of brakes. Different biological endpoints were investigated after exposing human alveolar epithelium A549 cells to the organic extracts: viability, cell cycle alterations and levels of intracellular reactive oxygen species (ROS). The particulate extracts from the wear of low steel brake pads induced greater decreases in cell viability. It was observed that cytotoxicity is more dependent on the individual composition of PAHs than on the global concentration. Exhaust samples from heavy-duty Euro V vehicles induced more toxic effects than Euro VI. Among Euro V vehicles, the exhaust of GTL was the most toxic. The composite weekly sample of the urban background atmosphere showed to be extremely toxic, decreasing cell viability to 2.66%, while the daily road tunnel samples caused a decrease of up to 83.6% at most. In the particulate extracts of the urban background atmosphere, retene and naphthalene were found, which were absent or present at trace levels in the tunnel. Irrespective of the sample, although some changes were observed in the A549 cell cycle after 24 h exposure in all the phases, the differences in the mean values were not great enough to exclude the possibility of random variability. When the results from the three phases (G0/G1, S and G2/M) of the cells exposed to all PM extracts were compared to the control, no statistically significant difference was detected. Regardless of the sample type, no significant increases in cellular ROS levels were observed either.

An Analysis of a Family Medicine Residency Program's Social Media Engagement During the 2021-2022 Match Cycle.

The COVID-19 pandemic affected the 2021 and 2022 residency recruitment cycles. Many programs rapidly shifted their recruitment efforts to include a greater presence on social media (SoMe), assuming that applicants would use these avenues as supplemental sources of information. As this represents a deviation from traditional recruitment efforts, our research team sought to analyze social media trends during the 2021-2022 family medicine virtual Match. We obtained social media analytics from our program's Facebook, Instagram, and Twitter accounts to trend user engagement as well as sources of traffic to our program's website. Our study shows the ratio of users reached per post correlated with Instagram and Twitter more than Facebook. The most users reached per post were in June, October, and February, corresponding to when Electronic Residency Application Service (ERAS) application opened, when interview invitations were mostly extended, and rank order list submission. GME website traffic sources revealed that Google was the greatest driver to our website, more than the three SoMe platforms combined. Our findings suggest Instagram and Twitter engage more users per post compared to Facebook, and user engagement appeared more aligned with the Match cycle timeline than the number of posts generated. It is important to continue to explore effective ways for applicants and programs to engage with one another in the ongoing uncertainty of virtual interviewing.

Gas‐phase kinetics, POCPs, and an investigation of the contributions of VOCs to urban ozone production in the UK

AbstractAmbient concentrations of 22 volatile organic compounds (VOCs) measured at London Marylebone Road (LMR), an urban traffic site, and London Eltham (LE), an urban background site, were analyzed over a period of 23 years (1997–2019) to assess the impact of pollution control strategies. A significant decrease in ambient concentration is seen for the majority of VOCs analyzed with total VOC burden decreasing by 76% and 59% for LMR and LE, respectively, across the period studied. This is likely as a result of legislative controls. This analysis was extended to consider the dominant contribution of VOCs to ozone formation at the sites utilizing photochemical ozone creation potential (POCP) values. Similarly, the overall reactivity of the VOC burden at the sites has resulted in a significant decrease of 11% and 7% per year in ozone formation potential (OFP) for LMR and LE, respectively. At LMR, the declines in OFP for VOCs associated with road traffic emissions are all in good agreement at 11%–13% decrease per year. Reasonable agreement is also seen at LE with a decrease of 6%–11% per year in OFP of the VOCs related to traffic sources. VOCs related to non‐traffic sources, namely ethane and propane from natural gas leakage, did not see a significant decline over the study period at either site. The variation and composition of the overall VOC burden was compared across three decadal time periods (1997–2000, 2001–2010, 2011–2019) and saw an increase in significance of these pollutants at both sites. At LMR, ethane and propane moved from the fifth and eleventh largest contributors to total VOC burden in 1997–2000 to the first and second largest contributors in 2011–2019. At LE, a similar trend is seen with ethane and propane becoming the first and second largest contributors in the most recent time period, up from second and eighth at the beginning of the dataset. The similarity between these sites suggests such pollutants are not sufficiently controlled under current legislation. The increase in significance of ethane and propane was mirrored in their contribution to ozone generation potential at both sites but ethene continues to dominate in contribution to OFP. At LMR, ethene dominates by a factor of 4 and 5 compared with ethane and propane, respectively, however, at LE, ethene dominates to a lesser extent over ethane and propane at factors of 1 and 3, respectively. Alkanes are typically considered to be less important in the context of OFP due to their low reactivity in comparison to other VOCs. Analysis presented herein demonstrates the negative impact of ignoring such emissions as their influence begins to grow such that alkanes now represent 3 of the 5 highest contributors to tropospheric ozone formation at both sites (in order of contribution at LMR: ethene > propene > n‐butane > ethane > propane; and LE: ethene > ethane > n‐butane > propane > propene). The importance of high‐quality gas‐phase kinetic studies to determine the impact of VOCs in ozone production is clear and the usefulness of metrics such as POCPs is demonstrated.

Reinforcement learning-based allocation of fog nodes for cloud-based smart grid

Real-time monitoring in smart grids requires efficient handling of massive amount of data. Fog cloud nodes can be strategically located within the smart grid to: pull readings from smart meters, implement local processing and control, and make all data available to the smart grid control center with minimum overall latency. Unlike existing studies in literature, we propose a novel Fog node allocation strategy that is tightly coupled with the power grid structure, and hence, accounts for the spatial distribution of data traffic sources (e.g., smart meters) within the power grid. Furthermore, the allocation strategy considers the diverse latency requirements of fixed scheduling and event driven data services within the power grid. The proposed allocation strategy first implements an unsupervised machine learning approach to determine initial number and locations of Fog nodes that can serve the data traffic with minimum overall latency. Then, a reinforcement-based mechanism is applied to minimize the required number of Fog nodes, and hence capital cost, through efficient mapping between Fog nodes and smart meters while still complying with the latency requirements. Our simulation studies demonstrate that a 50% reduction in required number of Fog nodes can be achieved while minimizing overall latency when the proposed allocation strategy is adopted.

Impact of urban viaducts on the vertical distribution of fine particles in street canyons

In the urbanization process, the viaduct has been regarded as an effective way to relieve metropolis traffic pressures in the urban area. However, due to the double emission source from elevated- and ground-road vehicles, the viaduct-built environment inevitably deteriorates the street canyon's air quality. Besides, the emitted air pollutants are trapped in such street canyons for extended periods. With this consideration, we used measured data to explore the impact of the viaduct on the vertical distribution of PM2.5 in street canyons. First, the experiments were conducted in a residential building near the inner ring of a viaduct in Shanghai, China. Next, the vertical distribution of PM2.5 and its diurnal variation were revealed based on these data. The results indicated the bimodal distribution patterns in the vertical profiles of PM2.5 mass concentrations, with the lower peak at height of 5 m under the viaduct and the upper peak at height of 10 m above the noise barrier on the viaduct. Further, the impact of the viaduct on the vertical distribution of PM2.5 was investigated. Results from both observation and simulation are consistent, revealing that 21–23% of PM2.5 was trapped beneath the viaduct, and the noise barrier causes the PM2.5 to decrease by 4–5%. The traffic source on the viaduct contributes 20–40% of the PM2.5. This study revealed the dispersion patterns of PM2.5, and the impact of the viaduct on it, which could be beneficial to optimizing the viaduct and the noise barrier to release traffic-related air pollutants in street canyons.

'Source-specific' air pollution and risk of stroke in Denmark.

Long-term air pollution is a risk factor for stroke. Which types and sources of air pollution contribute most to stroke in populations is unknown. We investigated whether risk of stroke differed by type and source of air pollution. We selected all persons aged >50 years and living in Denmark in the period 2005-17. We estimated running 5-year mean residential air-pollution concentrations of particulate matter <2.5 µm (PM2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO2). Pollutants were modelled as total air pollution from all emission sources, as well as apportioned into contributions from non-traffic and traffic sources. Hazard ratios (HRs) and CIs were estimated by using Cox proportional hazards models, adjusting for area-level and personal demographic and socio-economic covariates. We identified all primary strokes from hospital and mortality registers. The cohort numbered 2 million people and 94 256 cases of stroke. Interquartile ranges (IQR) of air pollution were associated with risk of stroke with HRs of 1.077 (95% CI: 1.061-1.094, IQR: 1.85 µg/m3) for PM2.5, 1.039 (1.026-1.052, IQR: 4248 particles/cm3) for UFP, 1.009 (1.001-1.018, IQR: 0.28 µg/m3) for EC and 1.028 (1.017-1.040, IQR: 7.15 µg/m3) for NO2. Traffic sources contributed little to the total exposure. HRs associated with air pollution from traffic were close to the null, whereas non-traffic sources tended to be associated with HRs higher than those for total air pollution, e.g. for non-traffic PM2.5, the HR was 1.091 (1.074-1.108). Air pollution, including UFP, was associated with risk of stroke. The risk appeared attributable mainly to air pollution from non-traffic sources.

Quantitative Source Apportionment of Potentially Toxic Elements in Baoshan Soils Employing Combined Receptor Models.

Arable soils are crucial for national development and food security; therefore, contamination of agricultural soils from potentially toxic elements (PTEs) is a global concern. In this study, we collected 152 soil samples for evaluation. Considering the contamination factors and using the cumulative index and geostatistical methods, we investigated the contamination levels of PTEs in Baoshan City, China. Using principal component analysis, absolute principal component score-multivariate linear regression, positive matrix factorization, and UNMIX, we analyzed the sources and quantitatively estimated their contributions. The average Cd, As, Pb, Cu, and Zn concentrations were 0.28, 31.42, 47.59, 100.46, and 12.36 mg/kg, respectively. The Cd, Cu, and Zn concentrations exceeded the corresponding background values for Yunnan Province. The combined receptor models showed that natural and agricultural sources contributed primarily to Cd and Cu and As and Pb inputs, accounting for 35.23 and 7.67% pollution, respectively. Industrial and traffic sources contributed primarily to Pb and Zn inputs (47.12%). Anthropogenic activities and natural causes accounted for 64.76 and 35.23% of soil pollution, respectively. Industrial and traffic sources contributed 47.12% to pollution from anthropogenic activities. Accordingly, the control of industrial PTE pollution emissions should be strengthened, and awareness should be raised to protect arable land around roads.

Source Apportionment and Model Applicability of Heavy Metal Pollution in Farmland Soil Based on Three Receptor Models.

The identification of the source of heavy metal pollution and its quantification are the prerequisite of soil pollution control. The APCS-MLR, UNMIX and PMF models were employed to apportion pollution sources of Cu, Zn, Pb, Cd, Cr and Ni of the farmland soil in the vicinity of an abandoned iron and steel plant. The sources, contribution rates and applicability of the models were evaluated. The potential ecological risk index revealed greatest ecological risk from Cd. The results of source apportionment illustrated that the APCS-MLR and UNMIX models could verify each other for accurate allocation of pollution sources. The industrial sources were the main sources of pollution (32.41~38.42%), followed by agricultural sources (29.35~31.65%) and traffic emission sources (21.03~21.51%); and the smallest proportion was from natural sources of pollution (11.2~14.42%). The PMF model was easily affected by outliers and its fitting degree was not ideal, leading to be unable to get more accurate results of source analysis. The combination of multiple models could effectively improve the accuracy of pollution source analysis of soil heavy metals. These results provide some scientific basis for further remediation of heavy metal pollution in farmland soil.

Identifying Anthropogenic Sources of Heavy Metals in Alpine Peatlands over the Past 150 Years: Examples from Typical Peatlands in Altay Mountains, Northwest China.

Alpine mountain peatlands are valuable archives of climatic and anthropogenic impact. However, the impacts of human activities on the Altay peatlands are poorly documented. Therefore, studying heavy metal (HM) concentrations, evaluating HM pollution levels, and identifying the sources in the Altay Mountain peatlands are crucial for revealing the intensity of human activities. The present study was performed on two peatland profiles: Jiadengyu (JDY) and Heihu (HH). The contents of HM and 210Pb and 137Cs dating technologies were used to construct a profile of anthropogenic pollutant distributions in the peatlands. Furthermore, the enrichment factor (EF) and geo-accumulation index (Igeo) of selected HMs were used to evaluate the risk assessment of HMs. The association of metals and assignment of their probable sources were examined using principal component analysis (PCA) and a positive matrix factorization model (PMF). The results showed that the concentrations of elements Cu, Zn, Cr, Pb, Ni, and As were at high levels in the two peatlands of the Altay Mountains, while the elements Hg and Cd were in low concentrations. Moreover, the concentrations of Cu, Cd, Hg, and Sb were higher than the background values of local element and posed a high environmental risk to the ecosystem. Combined with the results of the chronology, the peatland records indicated considerable growth in HMs concentrations from 1970 to 1990 related to recent anthropogenic activities. Additionally, the main sources of HMs are mining activities, domestic waste, and traffic sources in the two peatlands. Due to the environmental protection policies implemented since 2010, the natural processes have been the primary origin of HMs in peatlands, while emissions of industrial, agricultural, and domestic waste were still fundamental sources. The results of this study describe the sedimentary features of HMs in alpine mountains, and the data provide an essential theoretical basis for the evolutionary process through the characteristics of HM deposition.

Characteristics of Soil Heavy Metal Pollution and Health Risk Assessment in Urban Parks at a Megacity of Central China

In this study, we compared the concentrations of the heavy metals Cd, Cr, Cu, Zn, Ni, and Pb in the surface soils of urban parks in Wuhan, Hubei Province, with those in the surface soils of urban parks worldwide. The soil contamination data were assessed using enrichment factors and spatial analysis of heavy metals using inverse distance weighting and quantitative analysis of heavy metal sources with a positive definite matrix factor (PMF) receptor model. Further, a probabilistic health risk assessment of children and adults using Monte Carlo simulation was performed. The average Cd, Cr, Cu, Zn, Ni, and Pb concentrations in the surface soils of urban parks were 2.52, 58.74, 31.39, 186.28, 27.00, and 34.89 mg·kg-1, respectively, which exceeded the average soil background values in Hubei. From the inverse distance spatial interpolation map, heavy metal contamination was primarily observed to be present to the southwest of the main urban area. The PMF model resolved four sources: mixed traffic and industrial emission, natural, agricultural, and traffic sources, with relative contributions of 23.9%, 19.3%, 23.4%, and 33.4%, respectively. The Monte Carlo health risk evaluation model demonstrated negligible noncancer risks for both adult and child populations, whereas the health effects of Cd and Cr on children were a concern for cancer risks.

Potential risks, source apportionment, and health risk assessment of dissolved heavy metals in Zhoushan fishing ground, China

Dissolved heavy metal pollution in the ocean is one of the most severe environmental concerns; however, the potential sources of heavy metals and the resulting health risks are not fully understood. To explore the distribution characteristics, source apportionment, and health risks of dissolved heavy metals (As, Cd, Cu, Hg, Pb, and Zn) in the Zhoushan fishing ground, this study analyzed heavy metals in surface seawater during the wet and dry seasons. The concentrations of heavy metals varied greatly between seasons, and the mean concentration in the wet season was generally higher than that in the dry season. A positive matrix factorization model coupled with correlation analysis was applied to identify promising sources of heavy metals. Four potential sources (agricultural, industrial, traffic, atmospheric deposition, and natural sources) were identified as the determinants of the accumulation of heavy metals. The health risk assessment results revealed that non-carcinogenic risk (NCR) for adults and children were acceptable (HI < 1), and carcinogenic risk (CR) were at a low level (1 × 10−6 < TCR ≤ 1 × 10−4). The source-oriented risk assessment indicated that industrial and traffic sources were the main sources of pollution, contributing 40.7 % of NCR and 27.4 % of CR, respectively. This study proposes forming reasonable, effective policies to control industrial pollution and improve the ecological environment of Zhoushan fishing grounds.

Vertical Pollution Characteristics and Source Analysis of Soil PAHs in Different Land Use Types

In order to study the vertical pollution characteristics of polycyclic aromatic hydrocarbons (PAHs) in soils of different land use types in suburban areas of Nanjing, 15 types of controlled PAHs were studied in each section (0-100 cm) of soils from six different land use types, including a vegetable field, forestland, residential area, urban land, paddy field, and industrial area. The vertical distribution and composition characteristics, influencing factors, and sources of PAHs were analyzed. The results showed that:the total concentrations of Σ15PAHs in the six sampling site profiles were as follows:vegetable field (69.3-299.2 μg·kg-1), forestland (20.8-128.3 μg·kg-1), residential area (30.7-142.1 μg·kg-1), urban land (185.6-1728.7 μg·kg-1), paddy field (208.3-693.0 μg·kg-1), and industrial area (165.6-739.2 μg·kg-1). There was no pollution in the residential area or forestland and a light pollution level in the vegetable field, medium pollution level in the paddy field and industrial area, and more serious pollution in the urban land. Soil PAHs were mainly distributed in the surface or subsurface layer, except in the residential area and urban land; however, they were still detected in the deep layers, and high-molecular-weight PAHs were dominant in most depths and sampling sites. The vertical distribution and migration of PAHs in soils were affected by molecular characteristics and component concentrations of PAHs, soil physical and chemical properties, and land use types. PMF source analysis indicated that coke sources, traffic sources, and coal combustion sources from human activities were the main sources of PAHs in this study region.

Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions

Abstract. This paper outlines the development and operation of Yeti, a bottom-up traffic emission inventory framework written in the Python 3 scripting language. A generalized representation of traffic activity and emission data affords a high degree of scalability and flexibility in the use and execution of Yeti, while accommodating a wide range of details on topological, traffic, and meteorological data. The resulting traffic emission data are calculated at a road-level resolution on an hourly basis. Yeti is initially applied to traffic activity and fleet composition data provided by the senate administration for the city of Berlin, which serves as the region of interest, where the Yeti-calculated emissions are highly consistent with officially reported annual aggregate levels, broken down according to different exhaust and non-exhaust emission modes. Diurnal emission profiles on select road segments show not only the dependence on traffic activities but also on road type and meteorology. These road-level emissions are further classified on the basis of vehicle categories and Euro emission classes, and the results obtained confirmed the observations of the city of Berlin and subsequent rectifications.

Performance Enhancement of MANET based on Cross-layered Reconfigurable Hierarchical Routing Protocol

High speed data communication is the demanding factor in both commercial and defence applications. Several algorithms are proposed to support the high-speed data exchange while ensuring the quality, performance and reliability. However, there is still a gap, citing various compatibility issues with variety of transceiver technologies. This paper proposes a novel algorithm for enhancing the performance of mobile ad-hoc networks using Free-Space Optics (FSO). The FSO has the natural ability to the interference while capable of large bandwidth and excellent compatibility. Low power and adaptability are the features with which it has contributed to the latest technologies like storage area network, wireless area network etc. The proposed work uses optical spheres with a multi-transceiver system and a cross-layered reconfigurable routing mechanism. Parameters such as delay, residual energy, throughput, and drop are verified for the Crosslayered Reconfigurable Hierarchical Routing Optical Sphere (CRHROS) protocol for varying numbers of optical transceivers. The proposed work also compares the performance of two traffic sources, Constant Bit Rate (CBR) and Variable Bit Rate (VBR), for the proposed algorithm.

Loudspeaker modeling using CadnaA in an urban environment

CadnaA is traditionally used to model environmental noise sources, such as traffic, trains, and industrial noise sources. In this presentation, we will talk about past experiences using CadnaA to model outdoor noise levels from loudspeakers at music venues in an urban environment. This noise modeling was validated by comparing to “real world” measured data.

Realistic traffic model for urban environments based on induction loop data

As we gradually move towards smarter cities, having greater control of the traffic in the city becomes of utmost importance. In addition, to efficiently manage such traffic, it is critical to be able to predict the impact of different traffic policies, and potential changes to the city road systems structure. To this end, accurate traffic simulation models must be derived that can help in this task. This paper presents a tool that aims to improve the representativeness of traffic simulations by generating realistic Origin-Destination (OD) traffic matrices. In particular, we focus on cities whose source of traffic information are the induction loop detectors deployed through the different streets and avenues of the city. By comparing against the widely used DFROUTER tool, part of the SUMO open-source traffic simulation package, we show how we are able to improve the traffic model accuracy significantly. Specifically, we achieved more realistic route lengths and a better distribution of traffic sources and destinations.

Built environment factors predictive of early rapid lung function decline in cystic fibrosis.

The extent to which environmental exposures and community characteristics of the built environment collectively predict rapid lung function decline, during adolescence and early adulthood in cystic fibrosis (CF), has not been examined. To identify built environment characteristics predictive of rapid CF lung function decline. We performed a retrospective, single-center, longitudinal cohort study (n = 173 individuals with CF aged 6-20 years, 2012-2017). We used a stochastic model to predict lung function, measured as forced expiratory volume in 1 s (FEV1 ) of % predicted. Traditional demographic/clinical characteristics were evaluated as predictors. Built environmental predictors included exposure to elemental carbon attributable to traffic sources (ECAT), neighborhood material deprivation (poverty, education, housing, and healthcare access), greenspace near the home, and residential drivetime to the CF center. The final model, which included ECAT, material deprivation index, and greenspace, alongside traditional demographic/clinical predictors, significantly improved fit and prediction, compared with only demographic/clinical predictors (Likelihood Ratio Test statistic: 26.78, p < 0.0001; the difference in Akaike Information Criterion: 15). An increase of 0.1 μg/m3 of ECAT was associated with 0.104% predicted/yr (95% confidence interval: 0.024,0.183) more rapid decline. Although not statistically significant, material deprivation was similarly associated (0.1-unit increase corresponded to additional decline of 0.103% predicted/year [-0.113, 0.319]). High-risk regional areas of rapid decline and age-related heterogeneity were identified from prediction mapping. Traffic-related air pollution exposure is an important predictor of rapid pulmonary decline that, coupled with community-level material deprivation and routinely collected demographic/clinical characteristics, enhance CF prognostication and enable personalized environmental health interventions.

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses

Ambient fine particulate matter (PM2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Chemical composition and potential sources of PM2.5 in Hanoi

The chemical composition of PM2.5 was monitored simultaneously at two sites, one in a general area of the city center and one at a roadside, in Hanoi, Vietnam, during August 2019–July 2020 using 220 daily (24 h) filter samples. PM mass, water soluble ions, trace elements, organic and elemental carbon and sugar anhydrides were measured. The annual average PM2.5 concentrations, 49 and 46 μg m−3 at the traffic and the general urban site, respectively, exceeded the national (25 μg m−3) and 2021 WHO limit values (5 μg m−3). Daily PM2.5 concentrations were the highest in winter when stagnant meteorological conditions prevailed. On average, half of the resolved mass was organic matter, of which about 40% was attributable to biomass burning, most likely rice straw field burning and domestic fuel combustion. One third of PM2.5 was secondary inorganic aerosol which was dominated by sulphate hence indicating a high contribution of stationary sources like coal combustion. The elemental carbon level was higher at the traffic site, except in April 2020 during the COVID-19 restrictions. Zinc was the most common trace element with high daily variations and large differences between the sites, and it often peaked with Cd, Cl− and Pb indicating contribution of industrial sources and/or coal combustion. The highest zinc concentrations appeared on a few days and likely originated from open burning of municipal solid waste. It appeared that scattered open waste and biomass burning, as well as coal combustion, are important sources causing spikes of PM2.5 pollution in Hanoi above the general levels caused by routine industrial and traffic sources, especially during stagnant winter days. Source contributions were further studied with positive matrix factorization producing six source factors: traffic (12%), local secondary inorganic aerosol (SIA, 18%), biomass burning (19%), industry (9%), long-range transported SIA (25%) and dust (17%).

Influence of Acid Mine Drainage Leakage from Tailings Ponds on the Soil Quality of Desert Steppe in the Northwest Arid Region of China

As decision-making tools helping to improve the understanding of soil quality, soil quality assessment and heavy metal pollution assessment are very important for the remediation of heavy metal soil pollution. In the past, soil quality and heavy metal pollution have been studied separately, and few studies have combined them. The desert steppe in the Northwest Arid Region is an important pasture resource in China, and its soil safety has always been the focus of attention. Therefore, to understand the impact of tailing stockpiles on the soil quality of desert steppe, this study analyzed 18 indicators in the sample and analyzed the soil quality status of desert steppe based on the soil quality index (SQI) and Nemerow pollution index (Pcom). The main conclusions are as follows. (1) The evaluation results of heavy metal soil pollution show that the heavy metals Cu, Ni, Cr and Cd are significant polluters, Mn is a moderate polluter and Zn is a slight polluter. The results of the positive matrix factorization model show that Cu and Ni come from industrial sources; Cr, Cd and Zn come from industrial and traffic sources; and Mn comes from natural sources. (2) Regarding the study area, the generated minimum data set contains clay, pH, soil organic matter, available phosphorus, urease and neutral phosphatase. (3) The results of the SQI show that the soil in the study area is grade V (SQI-TDSave (total data set) = 0.42; SQI-MDSave (minimum data set) = 0.39), and the soil condition is very poor. 4) The linear fitting results show that the SQI-MDS was positively correlated with the SQI-TDS (R2 = 0.79), and SQI-MDS and SQI-TDS were negatively correlated with the Pcom (R2 &gt; 0.6). Therefore, the leakage of acid mine drainage from tailings pond accumulation has led to a significant decline in the soil quality of this desert steppe, and effective ecological restoration measures are urgently needed to ensure the sustainable stability of the steppe ecosystem.