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This paper investigates the impact of the digital economy on urban environmental pollution by analyzing panel data from 283 prefecture-level cities in China from 2011 to 2019 and using the digital technology comprehensive pilot zone of China as a natural experiment. The results demonstrate that digital technology has a significant effect in reducing pollutant emissions and empowering urban environmental governance. The findings are proven to be robust based on various tests, including parallel trend, PSM-DID, and placebo tests. Our analysis further shows that digital technology is particularly effective in controlling pollution in old industrial areas, high digital areas, and low energy efficiency areas. We also find that the national digital technology integrated pilot zone can mitigate environmental pollution in prefecture-level cities by increasing public environmental awareness and encouraging green technology innovation. Moreover, our research indicates that digital technology-enabled urban pollution control can contribute to the formation of a new urbanization pattern in China. These findings provide valuable insights for promoting the digital economy and achieving the goal of carbon reduction in China. [ABSTRACT FROM AUTHOR]

The influences of airborne trace elements in urban dust on element concentrations and functional traits of Tilia cordata were examined. For the present study, the unwashed and washed leaves of T. cordata were collected to assess the concentration of metals in Katowice City, Poland, from sites of different traffic intensity and industry activity. The content of Al, Cd, Cr, Cu, Fe, Mn, Pb, Zn, C, and N was measured. Additionally, a number of functional traits such as photosynthetic pigment content, specific leaf area (SLA), leaf dry matter content (LDMC), and diseased areas of the leaves were determined to assess the impact of the polluters on the physiology of the trees and their resources acquisition strategy. We hypothesized that the photosynthetic pigments of T. cordata will decrease with the traffic and industry intensity, and the traits related to the resources acquisition and stress resistance will shift into a more conservative strategy. The Principal Component Analysis and the Inverse Distance Weighting (IDW) interpolation method helped to identify that the Fe, Zn, Al, and Cr were related mainly to traffic intensification and Pb to industrial activities. The results indicate that Katowice is considerably polluted by Zn (up to 189.6 and 260.2 mg kg−1 in washed and unwashed leaves, respectively), Pb (up to 51.7 and 133.6 mg kg−1), and Cd (up to 2.27 and 2.43 mg kg−1) compared to other cities worldwide. Also, a reduction of approximately 27% in the photosynthetic pigments was observed at the high-traffic and industrial sites. The trees from the mainly affected areas with heavy traffic and industry tend to apply a conservative resources strategy with a decrement in SLA and an increment in LDMC. In contrast, the opposite trend was observed at the less affected sites (high SLA, low LDMC). The study showed that unfavourable urban conditions can trigger a plastic response on multiple levels. Knowledge of the possible paths of adaptation to urban conditions of different plant species is nowadays crucial to appropriate urban greenery planning. [ABSTRACT FROM AUTHOR]

Societal Impact Statement Over half of Earth's human population lives in urban areas where pollution from fossil fuel combustion threatens urban air quality and public health. The isotopic composition of plant tissues can be used as a tool to estimate local variation in the amount of fossil fuel–derived carbon dioxide. We present a case study that examines this variation against the backdrop of historic discriminatory policies in Saint Paul, Minnesota, USA. Data suggest higher loads of atmospheric fossil carbon in neighborhood greenspaces that are situated closer to large roads, which often correspond with historical policies. Evidence of unequal fossil fuel combustion, and potentially pollution load, may precipitate changes in urban management or pollution mitigation strategies. [ABSTRACT FROM AUTHOR]

The content of 17 individual polycyclic aromatic hydrocarbons (PAHs) was analyzed in samples of background and urban soils obtained during a geochemical survey of the territory of Ulan-Ude in the summer of 2022 for the first time. The average content of PAHs in the urban soils is 801 ng/g, which is more than 8.5 times higher than the level in background chestnut soils. The soil cover is contaminated primarily with medium- and high-molecular-weight PAHs. The proportions of individual PAHs in the soils of Ulan-Ude range within 4–11% at an average value of 6%. The urban soil cover is found to have ten high-contrast anomalies with the sum of PAHs ranging from 3162 to 10 189 ng/g. The principal component analysis and ratios of PAHs have made it possible to identify the main types of PAH sources and their contribution to urban soil pollution. [ABSTRACT FROM AUTHOR]

As the world's second-largest economy, China has experienced rapid industrialization and urbanization, resulting in high energy consumption and significant carbon emissions. This development has intensified conflicts between human-land relations and environmental conservation, contributing to global warming and urban air pollution, both of which pose serious health risks. This study uses nighttime light (NTL) data from 2005 to 2019, along with scaling techniques and statistical analysis, to estimate city-scale energy carbon emissions over a 15-year period. Focusing on Northeast China, a traditional industrial region comprising 36 cities across three provinces, we examine spatial patterns of energy carbon emissions and assess spatiotemporal evolution through spatial autocorrelation and dynamic changes. These changes are further evaluated using standard deviation ellipse (SDE) parameters and SLOPE values. Additionally, the Tapio decoupling index is applied to explore the relationship between city-scale emissions and economic growth. Our findings for the 36 cities over 15 years are: (1) Heilongjiang shows low, declining emissions; Jilin improves; Liaoning has high, steadily increasing emissions. (2) The global spatial autocorrelation of energy carbon emissions is significant, with a positive Moran's I, while significant local Moran's I clusters are concentrated in Heilongjiang and Liaoning. (3) The greatest emission changes occurred in 2015, followed by 2019, 2005, and 2010. (4) Emission growth is fastest in Heilongjiang, followed by Liaoning and Jilin. (5) Tapio analysis shows positive decoupling in Heilongjiang, declining decoupling in Jilin, and no change in Liaoning. This study provides a quantitative basis for dual carbon goals and offers emission reduction strategies for government, industry, and residents, supporting energy transition and sustainable urban planning. [ABSTRACT FROM AUTHOR]

Foraging increases predation risk. As such, prey frequently attend to potential predator cues when making decisions about foraging behaviour. Environmental cues, such as light levels, can impact predation risk, and populations from different environments may vary in how they respond to such cues. Here we experimentally manipulated foraging conditions for a frugivorous bat, the Jamaican fruit bat, to ask whether individuals rapidly alter their foraging behaviour based on potential predator cues and light levels. Specifically, we ran bats in multiple foraging trials across a night in which we varied the level of ambient light or predator cues (auditory or visual) and measured latencies to feed. We found that bats in a more urban population were most affected by simulated full moonlight, delaying their foraging behaviour. In contrast, bats from a rural population were sensitive to simulated urban light. Furthermore, rural bats were also more sensitive to potential predator cues and foraged more rapidly in the presence of novel objects and auditory predator cues. These results reveal variation across populations of the same species with respect to their response to potential predator cues, possibly indicating differences in their evaluations of foraging risks. • We tested responses to visual/auditory cues in urban vs rural Jamaican fruit bats. • Urban bats delayed foraging behaviour in simulated full moonlight. • Rural bats foraged more slowly in simulated urban light pollution. • Rural bats were more sensitive to potential predator cues than urban bats. • Rural bats also foraged more rapidly in the presence of various visual/auditory cues. [ABSTRACT FROM AUTHOR]

Some recent studies highlight that vehicular traffic and honking contribute to more than 50% of noise pollution in urban or sub-urban areas in developing countries, including Indian cities. Frequent honking has an adverse effect on health and hampers road safety, the environment, etc. Therefore, recognizing the various vehicle honks and classifying the honk of different vehicles can provide good insights into environmental noise pollution. Moreover, classifying honks based on vehicle types allows for the inference of contextual information of a location, area, or traffic. So far, the researchers have done outdoor sound classification and honk detection, where vehicular honks are collected in a controlled environment or in the absence of ambient noise. Such classification models fail to classify honk based on vehicle types. Therefore, it becomes imperative to design a system that can detect and classify honks of different types of vehicles to infer some contextual information. This paper presents a novel framework A C lassi H onk that performs raw vehicular honk sensing, data labeling, and classifies the honk into three major groups, i.e., light-weight vehicles, medium-weight vehicles, and heavy-weight vehicles. Raw audio samples of different vehicular honking are collected based on spatio-temporal characteristics and converted them into spectrogram images. A deep learning-based multi-label autoencoder model (MAE) is proposed for automated labeling of the unlabeled data samples, which provides 97.64% accuracy in contrast to existing deep learning-based data labeling methods. Further, various pre-trained models, namely Inception V3, ResNet50, MobileNet, and ShuffleNet are used and proposed an Ensembled Transfer Learning model (EnTL) for vehicle honks classification and performed comparative analysis. Results reveal that EnTL exhibits the best performance compared to pre-trained models and achieves 96.72% accuracy in our dataset. In addition, context of a location is identified based on these classified honk signatures in a city. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the relationship between air pollution (PM2.5) and a collection of features related to urban areas economic welfare and social‐wellbeing based on data collected from a number of 15 European capitals, for a seven years' period (2010–2017). The empirical analysis describes the correlation between the particulate pollution and welfare features in selected urban areas. Moreover, the PM2.5 pollutions may affect the economic and social development of these areas as, both entrepreneurs and population are inclined to relocate for a healthier environment. The models emphasize aspects related to the impact of PM 2.5 on different dimensions as follows: real estate rent values and land prices, restaurants food prices, community economic development, human welfare, as well as urban traffic. From the various correlations we have also discovered that for the urban areas included in the research, at early stages urbanization has the highest impact on air pollution. The findings of this study may offer hints for decision makers for their social and economic policy options. A clean urban environment will attract more skilled employees seeking for economic, social and environmental wellbeing. If the urban agglomerations authorities will fail to mitigate properly the air pollution issues the wellbeing will decrease along with the willingness of urban population to stay in such areas. [ABSTRACT FROM AUTHOR]

The expansion of urban areas has led to land-use changes that affect aquatic biodiversity and ecosystem processes through several ways, such as increased runoff, water pollution, habitat homogenization, and disturbance of the natural flow. It is well known that urbanization induces profound changes in freshwater macroinvertebrate communities, but relatively few studies have approached this topic using trait-based methods. This severely limits our ability to monitor and predict potential alterations of ecosystem processes. We here provide empirical evidence about the effects of urbanization-related changes on the trait composition and functional diversity of freshwater macroinvertebrates from Patagonia (Argentina). Macroinvertebrate sampling and environmental characterization were carried out in 13 study sites distributed across three water courses in the Futaleufú river basin. We found changes in environmental conditions over the urban impact gradient, in turn accompanied by variation in functional diversity and trait composition of aquatic macroinvertebrates. Specifically, we detected lower functional diversity in urban and post-urban reaches, mainly attributed to shifts in the distribution of taxa within the functional space, rather to the extirpation of functionally distinct taxa located at the edges of it (i.e., functional evenness and dispersion decreased, but functional richness remained constant). We also found signs of functional homogenization at the most impaired sites, where gatherers and tegument-breathing taxa dominated. These changes were mainly explained by conductivity, biological oxygen demand, and oxygen levels in the water column. [ABSTRACT FROM AUTHOR]

The distribution and composition of microplastics (MPs) in sediments provide a useful reflection of overall MP pollution for urban river systems. Sediment samples were collected from the Jinjiang River, the main tributary of the Minjiang River, to articulate the sources, distribution, and risk status of MPs. The results showed that the MPs in Jinjiang sediments were composed of polypropylene (PP), polyethylene (PE), polyethylene glycol terephthalate (PET), polystyrene (PS), and Rayon, with per kilogram of dry sediment (n/kg) ranged from 21 to 924 particles, and PP and PE were accounted for more than. MPs varied in colour, shape and size (100–5000 µm), although those observed were predominantly green, fragmented and about 1,000–5,000 µm. The dominant sources of MPs in sediments could be domestic waste and laundry effluents. The risk assessment for MPs showed that upstream and downstream were at moderate risk, while midstream was at low risk. This study can provide a reference for the management and control of MP pollution in urban rivers. [ABSTRACT FROM AUTHOR]

Urban air pollution, a combination of industry, traffic, forest burning, and agriculture pollutants, significantly impacts human health, plants, and economic growth. Ozone exposure can lead to mortality, heart attacks, and lung damage, necessitating the creation of complex environmental safety regulations by forecasting ozone concentrations and associated pollutants. This study proposes a hybrid method, RFNN-GOA, combining recurrent fuzzy neural network (RFNN) and grasshopper optimization algorithm (GOA) to estimate and forecast the daily ozone (O 3 ) in specific urban areas, specifically Kopački Rit and Osijek city in Croatia, aiming to improve air quality, human health, and ecosystems. Due to the intricate structure of atmospheric particles, modeling of O 3 likely poses the biggest challenge in air pollution today. The dataset used by the proposed RFNN-GOA model for the prediction of O 3 concentrations in each explored area consists of the following air pollutants, NO, NO 2 , CO, SO 2 , O 3 , PM 10 , and PM 2.5 ; and five meteorological elements, including temperature, relative humidity, wind direction, speed, and pressure. The RFNN-GOA method optimizes membership functions' parameters and the rule premise, demonstrating robustness and reliability compared to other identifiers and indicating its superiority over competing methods. The RFNN-GOA method demonstrated superior accuracy in Osijek city and Kopački Rit area, with variance-accounted for (VAF) values of 91.135%, 83.676%, 87.807%, 79.673% compared to the RFNN method's corresponding values of 85.682%, 80.687%, 80.808%, 74.202% in both training and testing phases, respectively. This reveals that RFNN-GOA increased the average VAF in Osijek city and Kopački Rit area by over 5% and 8%, respectively. [ABSTRACT FROM AUTHOR]

The digital economy, being a nascent technology, has exerted a substantial sway on how businesses are produced, how governments are run, how people live, etc. Considering this, additional investigation is required to gain a deeper comprehension of the connection between digital economic expansion and the impact of pollutant reduction, as well as the impact mechanism at play. Accordingly, using panel data from city-level data in China spanning the years 2011–2019 for analysis, this research explores the effects and mechanisms of digital economic growth on urban industrial pollution emission reduction. A two-way fixed effects model is applied. The outcomes demonstrate that a particular inflection point value determines how much the digital economy may reduce urban industrial pollutant emissions. Specifically, only when the digital economic development index surpasses 10 does it become viable to generate the emission reduction effect. The digital economic promotional influence on the decrease of urban industrial pollution emissions grows as industrial company service levels rise. Moreover, in regions with high market segmentation, in the eastern territories, and areas with strong policy support, the digital economy exhibits a lower inflection point for demonstrating its discharge lessening effects. [ABSTRACT FROM AUTHOR]

Car-sharing is a travel mode that can serve as an alternative to private cars, helping to reduce urban pollution. However, currently, there is a low willingness among travelers to use car-sharing, which is reflected in both low market penetration and user frequency. Therefore, it is essential for the government to encourage the use of car-sharing by providing subsidies. To better encourage the usage of car-sharing, this paper applies a two-fold evolutionary game model involving travelers and the government to explore the impact of subsidies on travelers' choices, and the factors that could affect the subsidies' efficiency. A simulation, using data from Beijing, was conducted to determine the implications of subsidy policies. The results show that a mileage-based subsidy and a fixed subsidy are applicable to travel of high and low mileages respectively, and under both subsidy modes, subsidies for trips with short duration or short pick-up and return time are more effective. Furthermore, we find that the efficiency of subsidies increases as the scale of car-sharing users, demand elasticity, or total number of travelers increases. Additionally, the subsidy levels should be lower than the environmental benefits of car-sharing but higher than the difference in travel costs between private cars and car-sharing. Future work will involve other game players such as car-sharing operators in order to draw deeper conclusions, and will involve the collection of data from more countries and cities to develop the robustness of the conclusions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has provided an opportunity to examine the impact of reduced human activity on air quality. This study assesses the levels of particulate matter (PM10) in three cities—Bucharest, Brașov, and Iași—during the pandemic restrictions in 2020, comparing them with data from the pre-pandemic period (2017–2019) and post-lockdown period (2021–2022). The results show a significant decrease in PM10 levels during the lockdown, which is closely associated with reduced traffic and mobility. Notably, while PM10 concentrations initially spiked at the beginning of 2020, they markedly declined following the enforcement of lockdown measures, during which mobility to workplaces in these cities decreased by about 60% in Bucharest, 50% in Brașov, and 45% in Iași. Health risks related to PM10 exposure were evaluated using the hazard quotient method, following EU and WHO guidelines. Despite the reduction in pollution levels in 2020, the findings suggest long-term human health risks for residents of these cities. This research highlights the critical need for sustainable strategies to address air quality issues in urban areas and protect public health. [ABSTRACT FROM AUTHOR]

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022. One-second data were aggregated to 377,113 8 s road segments, and 8 s rolling medians were aggregated to hourly and daily levels for further analysis. We assessed the temporal variability of fine particulate matter (PM2.5), nitrogen monoxide (NO), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and carbon dioxide (CO2) concentrations at hyperlocal levels. The average daytime median concentrations of NO2 (28.4 ± 15.7 µg/m3) and PM2.5 (7.6 ± 4.7 µg/m3) exceeded the WHO twenty-four hours (24 h) Air Quality Guidelines in 49.4% and 9% of the 1-year sampling time, respectively. For the diurnal variation of measured pollutants, the morning (8:00) and early evening (18:00) showed higher concentrations for NO2 and PM2.5, mostly happening in the winter season, while the afternoon is the least polluted time except for O3. The low-percentile approach along with 1-h and daytime minima method allowed for decomposing pollutant time series into the background and local contributions. Background contributions for NO2 and PM2.5 changed along with the seasonal variation. Local contributions for PM2.5 changed slightly; however, NO2 showed significant diurnal and seasonal variability related to traffic emissions. Short-lived event enhancement (1 min to 1 h) accounts for 36.0–40.6% and 20.8–42.2% of the total concentration for NO2 and PM2.5. The highly polluted days account for 56.3% of total NO2, highlighting local traffic is the dominant contributor to short-term NO2 concentrations. The longer-lived events (> 8 h) enhancement accounts for 25% of the monitored concentrations. Additionally, conducting optimal hotspot analysis enables mapping the spatial distribution of "hot" spots for PM2.5 and NO2 on highly polluted days. Overall, this investigation suggests both background and local emissions contribute to PM2.5 and NO2 pollution in urban areas and emphasize the urgent need for mitigating NO2 from traffic pollution in Dublin. [ABSTRACT FROM AUTHOR]

Urban industrial pollution plays a dominant role in environmental pollution in China. Exploring the digital governance path of urban industrial pollution can provide strong support for improving environmental quality. This article empirically investigates the role and path of digitalization in the governance of urban industrial pollution from three dimensions: economic scale, structural scale, and technological scale. The results show that there is an inverted "U"-shaped relationship between digitalization and urban industrial pollution, with initial promotion followed by suppression. Among them, economic scale, industrial transformation and upgrading, and green innovation are the paths for digital governance of urban industrial pollution. In addition, there is a chain path of "green innovation-industrial transformation and upgrading" between the two. Through spatial Durbin model and regional heterogeneity analysis, it is found that digitalization has a spatial spillover effect on urban industrial pollution control, and eastern regions, regions with high economic development level and industrialized cities benefit more from digital urban industrial pollution control. The research conclusions of this article provide references for the Chinese government to formulate relevant policies, deepen the integration of digitalization and urban industrial pollution, and promote digital governance of urban industrial pollution. [ABSTRACT FROM AUTHOR]

The increase in noise emissions is associated with an increase in the population, with anthropic activities, and it is in urban centers where a series of effects on both the population and the environment occur. The present study covered the evaluation of the noise behavior in the city of Cuenca during 2019, for which monitoring was carried out in 31 points distributed in the city based on the average daily traffic, the ordinance of use and occupation of the land and the dynamics of the population. The national environmental standard TULSMA (Unified Text of Secondary Legislation of the Ministry of the Environment) was taken as a reference. To establish the comparison of the data collected with a (low-cost, noise level) sensor and a sound level meter, measurements were made in 6 monitoring stations established on the basis of noise complaints made by citizens to the autonomous decentralized municipal government of Cuenca (GAD) and the security conditions to place for the placement of the equipment. The results showed that noise, in the city of Cuenca during 2019, noise is above the TULSMA environmental standard in Zone EQ1 (100% of the measurements), Zone R1 (96% of the measurements), Zone CM (100% of the measurements) and in Zone ID3 / ID4 (72% of the measurements). There was a high correlation coefficient (r = 0.8) and determination coefficient (R2 >0.6), between the data collected with the sensor and the sound level meter. It is worth highlighting the use of the calibrated sound level meter when making sound measurements with various instruments, as it allows the data to be verified and validated. [ABSTRACT FROM AUTHOR]

Warsaw is among European cities with the worst atmospheric air quality, mainly due to very high pollution emitted by the residential sector and road traffic. This results in high concentrations of particulate matter and nitrogen oxides, often exceeding WHO standards. The paper discusses the current and expected effects of actions taken by the Warsaw authorities, to significantly improve air quality in the city. The policy directly addresses one of the UN Sustainable Development Goals (SDG 11, Sustainable Cities and Communities). The analysis presented in the paper consists of two stages. The first, covering the years 2018–2029, deals with the ongoing Clean Air Program, which assumes primarily the reduction, and ultimately the complete elimination, of coal combustion in all heat sources of the residential sector. This sector is widely identified as the main source of urban air quality degradation, especially in Polish cities due to the dominant share of coal in the fuel mix. The second part of the corrective measures, covering the period 2024–2034, primarily concerns the reduction of nitrogen oxide pollution, mainly from traffic. The latter takes into account the expected effects of the introduction of a Low-emission Zone (LEZ) in the city center (launched in July 2024) and implemented in five two-year stages, in which car emission limits will be gradually tightened. According to the analysis results, the implementation of the Clean Air Program can result in about a 20% reduction in annual average PM2.5 concentrations by 2024, with a small (about 9%) reduction in NOx. At the same time, a significant reduction in NOx levels can be achieved by full implementation of the LEZ, especially within the zone boundaries (more than 50%). An important factor here is the size of the zone. The paper compares the effectiveness of two being considered versions, differing in size zones. [ABSTRACT FROM AUTHOR]

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low-cost sensors, a fire broke out from an outbuilding containing roughly 3000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modeling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, and the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 min at an emission rate of 50 g/s of PM2.5. The emission was significantly greater than a 'normal' house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast-response numerical models at various compromised levels of accuracy, efficiency and cost. [ABSTRACT FROM AUTHOR]

Monitoring atmospheric pollution in urban areas is challenging because pollutant deposition occurs at short distances, requiring a large amount of sampling and analysis to characterize it. Ecological indicators can help overcome this problem, allowing us to select sites with the highest deposition of pollutants from the atmosphere. Nevertheless, a major gap is the temporal characterization of the accumulation rate of magnetic particles in ecological indicators, which is critical to understand if the bioaccumulation process is linear or if saturation occurs. To overcome this problem, Parmotrema perlatum lichens were magnetically and chemically studied in a pollution gradient over space and time. Lichen transplants were exposed over 18 weeks to a high-traffic road. Results show that magnetic properties and element composition reflected both distance from the road (nonlinear decrease of up to 100 m from source) and exposure time (increasingly linearly over the entire study period with eightfold increments), showing that up to 18 weeks, the accumulation rate remained constant over time, with no saturation occurring. Chemical analysis showed a strong linear relationship between the accumulation of zinc (Zn), antimony (Sb), manganese (Mn), copper (Cu) chromium (Cr) and magnetic susceptibility. Magnetization acquisition curves reveal a time-dependent low-coercivity component, interpreted as mainly related to nonexhaust, mostly brake abrasion particle emissions. It is concluded that the magnetic properties of lichen transplants can be used in urban environments to characterize the spatial and temporal patterns of the deposition of pollution metallic particles from the atmosphere. [ABSTRACT FROM AUTHOR]

Assessing air quality in urban areas is vital for protecting public health, and low-cost sensor networks help quantify the population's exposure to harmful pollutants effectively. This paper introduces an innovative method to calibrate air-quality sensor networks by combining CFD modeling with dependable AQ measurements. The developed CFD model is used to simulate traffic-related PM10 dispersion in a 1.6 × 2 km2 urban area. Hourly simulations are conducted, and the resulting concentrations are cross-validated against high-quality measurements. By offering detailed 3D information at a micro-scale, the CFD model enables the creation of concentration maps at sensor locations. Through regression analysis, relationships between low-cost sensor (LCS) readings and modeled outcomes are established and used for network calibration. The study demonstrates the methodology's capability to provide aid to low-cost devices during a representative 24 h period. The precision of a CFD model can also guide optimal sensor placement based on prevailing meteorological and emission scenarios and refine existing networks for more accurate urban air quality representation. The usage of cost-effective air quality networks, high-quality monitoring stations, and high-resolution air quality modeling combines the strengths of both top-down and bottom-up approaches for air quality assessment. Therefore, the work demonstrated plays a significant role in providing reliable pollutant monitoring and supporting the assessment of environmental policies, aiming to address health issues related to urban air pollution. [ABSTRACT FROM AUTHOR]

Because of its low‐lying location, urbanization, and inadequate infrastructure, Jakarta (Indonesia) has experienced an increase in annual flooding events, rising from an average of five significant floods per year in the 1990s to over 20 annually (2010–2020). With climate change exacerbating extreme weather events, Jakarta encounters escalating risks of flooding. Although the recurrent flooding is exacerbated by non‐point source (NPS) of pollution such as urban runoff and agricultural discharge that contribute to 40% of total pollutants leading to flood‐related issues in Jakarta, none has investigated this research gap. To reflect its novelty, this work explores the implications of climate change on the annual flooding in Jakarta by focusing on NPS and analyzes their impacts from social perspectives. This work also underscores the implications of flooding on livelihoods, health, and social cohesion in Jakarta. Focus group discussion with affected residents was used to shed light on the coping strategies employed in response to recurrent floods, ranging from community‐based initiatives to reliance on informal networks. The empirical findings show that the implications of flooding extend beyond physical damages. Displacement of communities, loss of livelihoods, disruption of essential services, and increased health risks are among the social impacts experienced by local residents. Vulnerable populations, including low‐income communities residing in informal settlements, bear their consequences. Economic losses from flooding amount to USD 500 million annually, impacting over 1 million residents. However, recent interventions have led to a 15% reduction in peak flood levels and a 20% reduction in flood duration in affected areas. Community resilience has also improved, with a 25% increase in flood insurance coverage and a 20% rise in community response initiatives. Overall, this study highlights that climate change exacerbates annual flooding in Jakarta, significantly impacting vulnerable communities through NPS pollution. Addressing the challenges requires integrated approaches combining effective pollution control, resilient infrastructure, and community engagement to mitigate social and long‐term environmental impacts. Practitioner Points: Climate‐induced flooding disproportionately affects vulnerable communities in Jakarta.Non‐point source pollution from urban runoff contributes to the severity of flooding in Jakarta.Waterborne diseases, disruption of livelihoods, and reduced access to clean water are major concerns identified in the study.The study highlights the importance of community‐based adaptation strategies to mitigate the impact of flooding and pollution. [ABSTRACT FROM AUTHOR]

It is of great significance to explore the causality between regional integration (RI) and PM2.5 pollution within urban agglomerations in the current pursuit of ecological civilization construction and high‐quality development. Using panel data of 285 prefecture‐level cities in China from 2003 to 2016, this study considers the expansion of the city economic coordination committee in Yangtze River Delta (YRDECC) as a quasi‐natural experiment of RI, and use a difference‐in difference method to explore the effect and inner mechanisms of RI on PM2.5 concentration. After a descriptive analysis of the spatial‐temporal variation trend of the PM2.5 concentration in the Yangtze River Delta urban agglomeration, the empirical results show that RI helps to alleviate 4.8% of the PM2.5 concentration overall. For the original cities, the reduction effect on the PM2.5 concentration is 5.2%, for the new cities, however, RI exacerbates 2.1% of the local PM2.5 concentration. A series of robustness tests confirm the validity of the baseline results, and further indicate that the effect of RI remains significant in the long term and starts to increase from the third year. Furthermore, the reduction effect of RI on PM2.5 concentration is more pronounced in cities with larger scales, more developed economies, and higher degrees of marketization. The mechanism analysis shows that industrial transfer, population migration and technological innovation are significant channels of RI that affect PM2.5 concentrations. The conclusions of this paper provide a new path to alleviate PM2.5 pollution and achieve ecological conservation and high‐quality development in the city cluster area. [ABSTRACT FROM AUTHOR]

In the present study we investigated the combined effect of flow intermittence and wastewater treatment plant (WWTP) effluent on leaf litter decomposition in two Mediterranean streams with permanent and intermittent flow regimes. The litter decomposition experiment was performed using black poplar litter bags where we measured litter mass loss, fungal biomass, aquatic hyphomycete sporulation and species richness and C:N ratio. Afterwards, the remaining litter material from the different treatments was offered to the shredder Potamophylax latipennis in a microcosm laboratory experiment, and its growth and consumption rates were studied. We hypothesised that drying would decrease leaf litter decomposition in the permanent stream more than in the intermittent stream and that WWTP effluent would compensate for drying effects when both stressors interacted. The results indicated that drying has the greatest impact on the permanent stream, decreasing decomposition, aquatic hyphomycete species richness, and leaf litter quality. In the intermittent stream, WWTP effluent decreases aquatic hyphomycete species richness, but drying increases it, showing an opposing effect and a synergistic interaction. In the permanent stream drying provoked an increase in the shredder consumption rate. Thus, the expected more frequent intermittence in rivers under climate change may threaten the processing of organic matter. [ABSTRACT FROM AUTHOR]

Urban pollution governance requires the joint participation of government, society, and enterprises, with the environmental information disclosure policy serving as a novel tool to promote multi-stakeholder engagement. This study aims to delve into the impact of the environmental information disclosure policy on regional environmental quality by using data from Chinese cities. Through analysis, the study gets the following conclusions. Firstly, the environmental information disclosure policy not only effectively reduces urban environmental pollution but also exhibits an apparent spatial spillover effect. The impact of this policy on air pollution in neighboring cities shows an inverted U-shaped pattern of first rising and then falling, with the optimal radius of this external effect estimated at 250 km. Secondly, the results of the mechanism test indicate that government regulatory efforts and clean industry alternatives are essential channels for curbing urban environmental pollution. Lastly, the heterogeneity test shows that the inhibitory effect of the environmental information disclosure policy on environmental pollution is more pronounced in civilized cities, cities in the "two control zones", sulfur dioxide control zones, and cities with high Pollution Information Transparency Index scores. [ABSTRACT FROM AUTHOR]

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This paper presents an analysis of NO2 emissions in Mashhad City utilizing statistical evaluations and the Cisco Network Model. The present study begins by evaluating NO2 emissions through statistical analysis, followed by the application of histograms and radar statistical appraisals. Subsequently, a model execution logic is developed using the Cisco Network Model to further understand the distribution and sources of NO2 emissions in the city. Additionally, the research incorporates managerial insights by employing Petri Net modeling, which enables a deeper understanding of the dynamic interactions within the air quality management system. This approach aids in identifying critical control points and optimizing response strategies, thus enhancing the overall effectiveness of urban air pollution mitigation efforts. The findings of this study provide valuable insights into the levels of NO2 pollution in Mashhad City and offer a structured approach to modeling NO2 emissions for effective air quality management strategies which can be extended to the other megacities as well. [ABSTRACT FROM AUTHOR]

Growing concern over microplastic pollution, driven by their widespread accumulation in the environment, stresses the need for comprehensive assessments. This study investigates the spatial and temporal distribution of microplastics in the Ikopa River (Antananarivo – Madagascar), which flows through a densely populated area, and examines their correlation with contamination levels in local fish species. By analyzing upstream and downstream stations across wet and dry seasons, only a notable increase in microplastic concentration downstream during the wet season was observed, ranging from 138.6 ± 9.0 to 222.0 ± 24.5 particles m−3, with polyethylene-co-vinyl acetate being the predominant polymer at 62.3 ± 5.13% of the total sampled polymers. This distribution underlines the impact of urban activities on pollution levels. Fish species, gambusia and Nile tilapia, were assessed for microplastic occurrence in gills and gastrointestinal tracts. Higher contamination rates were found in gambusia, enlightening the influence of feeding behaviour and fish habitat on microplastics contamination. Ingestion of microplastics directly from the water column was evident in both species, with the detection of high-density plastics such as polytetrafluoroethylene and polyvinyl chloride suggesting likely sediment contamination. This research highlights the widespread contamination of aquatic environments and its direct impact on local wildlife, pointing to a clear requirement for effective pollution management strategies. [ABSTRACT FROM AUTHOR]

The presence of polycyclic aromatic hydrocarbons (PAHs) pollution on urban road surfaces is one of the major environmental concerns. However, knowledge on the distribution variability of PAHs in road dusts (RDS) and stormwater is limited, which would restrict the further risk evaluation and mitigation implementation of PAHs in road stormwater runoff. This study collected RDS samples and stormwater samples on fourteen urban roads in Shenzhen, China. This study investigated the variation of sixteen PAHs species in RDS and stormwater, and further evaluated the intrinsic and extrinsic factors which influence PAHs accumulation on urban road surfaces. The research outcomes showed significant differences on spatial distribution of PAHs in RDS and in stormwater. The land use types, industrial, commercial and port areas and vehicular volume have a positive relationship with PAHs abundance while dust particle size showed a negative correlation with PAHs abundance. For two phases in stormwater, fluctuation of PAHs with the rainfall duration in total dissolved solid (TDS) was more intensive than in dissolved liquid phase (DLP). This indicated when PAHs attached to RDS enter stormwater, most of PAHs still tend to be on solid particles than in liquid. The study outcomes are expected to contribute to efficient designs of PAHs polluted stormwater mitigation. [ABSTRACT FROM AUTHOR]

Urban environment and air quality are changing primarily due to land use land cover (LULC) changes, economic activity, and urbanization. Air pollution has been increasingly acknowledged as a major issue for cities due to its extensive effects on health and well-being. As the second most populous city in the country, Lahore faces alarming levels of air pollutants, which induced this study to focus on the pervasive issue of air pollution in Lahore. For this, the study collected air pollutants data from the Environmental Protection Department of Punjab and analyzed them using the ARIMA model. In the research results, both the observed data and predictive models uncovered concerning trends in pollutant concentrations, ultimately portraying a concerning picture for air quality management. Carbon monoxide (CO) levels show a consistent rise, surpassing Pakistan's environmental standards by 2025. Similarly, nitrogen dioxide (NO2) concentrations escalate, exceeding prescribed standards. Ground-level ozone (O3) also demonstrates a substantial increase, surpassing standards by 2025. Both PM2.5 and PM10 exhibit marked upward trends, projected to exceed recommended limits, particularly PM10 throughout the study year. The Air Quality Index exhibits an observable upward trend, fluctuating between 70 and 442 from 2015 to 2020. Similarly, a positive correlation was found between population growth and land use conversion into residential areas. Projections suggest a continuous increase, potentially hitting a severe level of 500 during winter by 2025. These findings point to an impending air pollution crisis, demanding urgent action to address the hazardous situation in the city. The study recommends that urban air pollution should be reduced, and the negative health effects of air pollution should be minimized using vegetation barriers, screens, and greening initiatives. Strict regulations and monitoring initiatives need to be put in place in big cities to monitor pollution and vegetation. [ABSTRACT FROM AUTHOR]

Airborne particulate matter (PM) is known to have adverse health effects and is a growing concern in urban areas. Spatial and temporal variability is difficult to assess with the few air quality stations typically available in cities. As an alternative, tree bark acts as a passive captor on which PM is deposited. Magnetic susceptibility measurements can be used as a proxy indicator to estimate pollution from vehicle sources. We present the citizen science project called Ecorc'Air, in which volunteers collect plane tree bark samples, mainly in Paris, which are then sent to laboratories and used for various measurements. The project has developed since 2016, leading to the production of annual maps that identify variations in magnetic particle concentrations. The correlation between magnetic susceptibility and metal content has been verified using multi elemental analysis. Thanks to these numerous samples, we were able to identify areas with consistently high susceptibility values over time. We also quantified the decrease in susceptibility values with the distance between the tree and the road, as well as the shielding effect of parked cars on pedestrians. We showed trends in susceptibility variations over time along a specific well‐sampled road, suggesting that this type of sampling and measurement could be used to quantify variations in metallic pollution at a local scale. Finally, through interviews, we found that there is a growing interest and participation of city dwellers, especially those involved in local associations, to act in favor of environmental research, as well as of municipalities to offer support. Plain Language Summary: Airborne pollution caused by particulate matter (PM) is a growing concern in cities because of its negative effects on health. Air quality stations in cities are too few to give a detailed image of the distribution of pollution. However, PM is also deposited on trees. Tree bark can then act as captors, and their magnetic properties can measure the quantity of metallic particles deposited on them, and give an estimate of the pollution from motorized traffic. Here we present the citizen science project Ecorc'Air, in which volunteers collect plane tree bark fragments, which are then sent to laboratories and used for various measurements. Since its beginning in 2016, the project has enabled the production of annual maps showing detailed concentration of metallic particles in Paris at a local scale. The quantity of particles decreases with the distance between the tree and the road, and parked cars can act as a shield for PM on pedestrians. Individual volunteers have different motivations than volunteers in groups or associations. Municipalities supporting the project consider citizen sciences as a way to connect with their citizens on environmental issues and a source of data for air quality quantification. Key Points: We present the citizen science project Ecorc'Air, in which volunteers collect plane tree bark samples which are sent to laboratoriesThe project has led to the production of annual maps since 2016 that identify variations in magnetic particle concentrations in ParisThere is a growing interest and involvement in environmental research among urban dwellers, especially those involved in local associations [ABSTRACT FROM AUTHOR]

The dilemma between economic development and environmental protection has gained widespread attention, but limited research from the perspective of political business cycles exists. By utilizing detailed official turnover datasets and two-way fixed effect models, this study investigates the impact of political turnovers of city leaders on changes in urban PM2.5 (particulate matter 2.5) density in China. It examines how different stages of a leader's tenure contribute to these changes and considers their potential connection to the performance-based cadre evaluation system that drives government turnovers in China. The study finds that prior to turnover, mayors tend to relax environmental regulations, leading to an 1.5% increase in PM2.5 density. However, during the second years after the mayor has taken office, air quality improves, with a 1% decrease in PM2.5 density. The effect of political business cycles on air quality is heterogeneous across cities with varying financial conditions, innovative capacity, and population size. The findings provide evidence that environmental protection might be sacrificed for economic development in the period prior turnover, particularly in cities with lower development levels. These insights can assist the government in considering how political cycles and the heterogeneous regional characteristics can be adjusted to promote environmental protection. [ABSTRACT FROM AUTHOR]

The life quality of populations, especially in large agglomerations, is significantly reduced due to air pollution. Major sources of pollution include motor vehicles, industrial facilities and the burning of fossil fuels. A particularly significant source of pollution is thermal power plants and coal-fired power plants, which are widely used in developing countries. The Astana city in the Republic of Kazakhstan is a fast-growing agglomeration where air pollution is compounded by intensive construction and the use of coal for heating. The research is important for the development of urbanism in terms of ensuring the sustainable development of urban agglomerations, which are growing rapidly. Long memory in time series of concentrations of air pollutants (particulate matter PM10, PM2.5) from four stations in Astana using the fractal R/S analysis method was studied. The Hurst exponents for the studied stations are 0.723; 0.548; 0.442 and 0.462. In addition, the behavior of the Hurst exponent in dynamics is studied by the flow window method based on R/S analysis. As a result, it was found that the pollution indicators of one of the stations are characterized by the presence of long-term memory and the time series is persistent. According to the analysis of recordings from the second station, the series is defined as close to random, and for stations 3 and 4, anti-persistence is characteristic. The calculated Hurst exponent values explain the sharp increase in pollution levels in October 2021. The reason for the increase in polluting substances concentration in the air is the close location of thermal power plants to the city. The method of time series fractal analysis can be the ecological state indicator in the corresponding region. Persistent pollution time series can be used to predict the occurrence of a critical pollution level. One of the reasons for anti-persistence or the occurrence of a temporary contamination level may be the close location of the observation station to the source of contamination. The obtained results indicate that the fractal time series analysis method can be an indicator of the ecological state in the relevant region. [ABSTRACT FROM AUTHOR]

Urban air pollution poses a significant threat to human health, with metropolitan areas particularly affected due to high emissions from human activities. Particulate matter (PMx) is among the most harmful pollutants to human health, being composed of a complex mixture of substances related to severe pulmonary conditions. Urban green spaces play a vital role in mitigating air pollution by capturing PMx, and it is essential to select plant species with a high capacity for PMx accumulation to effectively enhance air quality. This study aimed to evaluate and compare the accuracy of two PMx quantification methods—light microscopy and filtration—which demonstrated a high correlation (R2 = 0.72), suggesting that both methods are reliable for assessing PMx accumulation on leaves. Light microscopy allowed for the visualization of PMx deposition, revealing the species warranting further analysis using the filtration method. Among the species analyzed, Euonymus japonicus, Ligustrum lucidum, Alnus glutinosa, Rubus ulmifolius, and Laurus nobilis demonstrated the highest total PMx accumulation, exceeding 50 µg cm−2, making them particularly valuable for air pollution mitigation. This study examined the correlation between leaf traits such as specific leaf area (SLA), leaf area (LA), leaf dissection index (LDI), and leaf roundness and PMx accumulation across the 30 different plant species. A multiple linear regression analysis indicated that these leaf traits significantly influenced PMx accumulation, with SLA and LA showing negative correlations and leaf roundness exhibiting a positive correlation with PMx deposition. In conclusion, this study highlights the importance of selecting plant species with specific leaf traits for effective air quality improvement in urban environments particularly in highly polluted areas, to enhance air quality and public health. [ABSTRACT FROM AUTHOR]

Fine particulate matter 2.5 (PM2.5) is a widely studied pollutant with substantial health impacts, yet little is known about the urban‐rural differences across the United States. Trends of PM2.5 in urban and rural census tracts between 2010 and 2019 were assessed alongside sociodemographic characteristics including race/ethnicity, poverty, and age. For 2010, we identified 13,474 rural tracts and 59,065 urban tracts. In 2019, 13,462 were rural and 59,055 urban. Urban tracts had significantly higher PM2.5 concentrations than rural tracts during this period. Levels of PM2.5 were lower in rural tracts compared to urban and fell more rapidly in rural than urban. Rural tract annual means for 2010 and 2019 were 8.51 [2.24] μg/m3 and 6.41 [1.29] μg/m3, respectively. Urban tract annual means for 2010 and 2019 were 9.56 [2.04] μg/m3 and 7.51 [1.40] μg/m3, respectively. Rural and urban majority Black communities had significantly higher PM2.5 pollution levels (10.19 [1.64] μg/m3 and 9.79 [1.10] μg/m3 respectively), in 2010. In 2019, they were: 7.75 [1.1] μg/m3 and 7.09 [0.78] μg/m3, respectively. Majority Hispanic communities had higher PM2.5 levels and were the highest urban concentration among all races/ethnicities (8.01 [1.73] μg/m3), however they were not the highest rural concentration among all races/ethnicities (6.22 [1.60] μg/m3) in 2019. Associations with higher levels of PM2.5 were found with communities in the poorest quartile and with higher proportions of residents age<15 years old. These findings suggest greater protections for those disproportionately exposed to PM2.5 are needed, such as, increasing the availability of low‐cost air quality monitors. Plain Language Summary: PM2.5 is a well‐known air pollutant that impacts human health. However, little is known about how it differs between urban and rural areas in the United States (U.S). This study investigated these differences between 2010 and 2019 at a level that had not been assessed before across the United States. Rural areas generally had lower PM2.5 levels compared to urban areas and the pollution decreased faster in rural areas during this time. Both rural and urban areas with higher proportions of residents that are Black, Hispanic, and in poverty had higher PM2.5 levels. There were no consistent patterns between the age distribution of urban or rural census tracts and PM2.5 levels. Key Points: Between 2010 and 2019, PM2.5 levels were consistently lower in rural communities than in urban communities across the United StatesHigh percentage Black communities had significantly higher PM2.5 pollution levels in both rural and urban census tractsGreater protection from air pollution for socially disadvantaged communities in both rural and urban settings is warranted [ABSTRACT FROM AUTHOR]

During the first two decades of the twenty‐first century, we analyze the expansion of urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol products from NASA's Moderate Resolution Imaging Spectroradiometer. Our approach involves both direct utilization and fusion with in situ observations for a comprehensive characterization. We also examined how social vulnerability within the HMA changed during the study period and whether the synergy of UHI, UPI, and social vulnerability enhances environmental inequalities. We found that urban land cover within the HMA increased by 1,345.09 km2 and is accompanied by a 171.92 (73.93) % expansion of the daytime (nighttime) UHI. While the UPI experienced an overall reduction in particulate pollution, the magnitude of change is smaller compared to the surroundings. Further, the UPI showed localized enhancement in particulate pollution caused by increases in vehicular traffic. Our analysis found that the social vulnerability of the HMA urban regions increased during the study period. Overall, we found that the urban growth during the first two decades of the twenty‐first century resulted in a synergy of UHI, UPI, and social vulnerability, causing an increase in environmental inequalities within the HMA. Plain Language Summary: We used a combination of satellite and ground‐based observations to study how urban area expansion in Houston, Texas affects urban heat, pollution, and social vulnerability. We found that in the past two decades, Houston has added to its urban land cover by almost twice the area of New York City. This resulted in warmer conditions during the daytime which persisted during the night. Although there was an overall decrease in particulate pollution, our research identified pockets of heightened traffic activity that offset these improvements. We also found social vulnerability increased during the last two decades. We find the combined effect of increased heat stress, pollution and vulnerability leads to increased environmental inequalities. Key Points: The rapid urbanization of Houston expands the urban heat and pollution islands, raising exposure to high temperatures and poor air qualityCommunities with highest social vulnerability are most impacted by the adverse effects of urban heat and pollution islandsThe Clean Air Act's efficacy is locally diminished by Houston's urban pollution island [ABSTRACT FROM AUTHOR]

African cities grapple with urban air pollution from traffic‐related air pollutants (TRAPs). This study investigated TRAPs concentration variations at traffic intersections (TIs) in Ibadan, Nigeria. AERMOD model was employed to examine TRAPs dispersion at 25 selected TIs, considered as volume sources. Seasonal concentration distributions of six pollutants (CO, NO2, SO2, TVOCs, PM2.5, and PM10) were determined using meteorological, topographical, and pollutants' emission rates in AERMOD. Estimated peak concentrations of the studied pollutants were generally higher in the rainy season than dry season, surpassing the air quality standards set by World Health Organization (WHO) and Nigeria's National Environmental Standards and Regulations Enforcement Agency (NESREA) during the rainy and dry seasons except SO2 (24 h) concentration which did not exceed the NESREA standard. This study highlighted TIs as significant contributors to air quality degradation in both seasons studied in Ibadan and showed AERMOD's suitability for air dispersion studies. [ABSTRACT FROM AUTHOR]

The rapid development of new energy vehicles and Lithium-Ion Batteries (LIBs) has significantly mitigated urban air pollution. However, the disposal of spent LIBs presents a considerable threat to the environment. Recycling these waste LIBs not only addresses the environmental issues but also compensates for resource shortages and generates substantial economic benefits. Current recycling processes primarily focus on the extraction of valuable metals, often overlooking the treatment of residual waste post-extraction. This project targets the iron phosphate (FePO4) derived from waste lithium iron phosphate (LFP) battery materials, proposing a direct acid leaching purification process to obtain high-purity iron phosphate. This purified iron phosphate can then be used for the preparation of new LFP battery materials, aiming to establish a complete regeneration cycle that recovers lithium carbonate and iron phosphate from waste LFP materials for the production of LFP. The study investigates process parameters such as acid types and concentrations, leaching time, and the number of leaching cycles. The results demonstrate that, after purification, the levels of impurity metals decrease while the iron content increases correspondingly. Under optimized experimental conditions, the dilute sulfuric acid leaching rates of Al, Cu, Ca, and Ni reached 36.0%, 51.4%, 89.5%, and 90.9%, respectively. Furthermore, hydrothermal treatment in dilute phosphoric acid achieved leaching rates of 87.9%, 85.8%, 98.4%, and 99.1% for Al, Ca, Cu, and Ni, respectively. The microstructure characterization revealed significant changes in phase and grain morphology during the leaching process in dilute phosphoric acid, which are likely associated with the liberation of impurity atoms from the lattice. These findings indicate that acid leaching is highly effective in removing impurities from the iron phosphate recycled from waste LIBs. [ABSTRACT FROM AUTHOR]

\nHIGHLIGHTSThis research examines particulate matter with a diameter of 2.5 micrometers (PM2.5) and ozone (O3) variation across the climatic mesoregions of Alagoas. Mean PM2.5 and O3 concentrations across three mesoregions were as follows: East (5.91; 44.22 μg.m−3), Hinterland (6.90; 44.18 μg.m−3), and Arid (7.03; 44.23 μg.m−3). Spatial and temporal variations were observed, with PM2.5 concentrations highest in the northwest (NW) and O3 concentrations in the east (E), influenced by local sources, weather, and transportation. Differences between rainy and dry years were noted, attributed to biomass burning and dust particle transport. This study establishes a baseline for understanding air quality, lacking monitoring stations, aiding policymaking. It provides insights into PM2.5 and O3 dynamics, with PM2.5 concentrations highest in the NW and lower O3 concentrations in the E. Temporal variations emphasize the need for dynamic monitoring. Positive correlations between PM2.5 and O3 highlight complex relationships. Practical implications include proactive policymaking and the necessity for monitoring stations. Rigorous statistical methodologies inform model selection, enhancing environmental data understanding. Despite changes in land use, studies on extreme probability distributions are limited, emphasizing the need for robust methodologies for environmental data analysis to address air pollution challenges effectively in Alagoas. Spatio-temporal variability of the airborne pollutant criteria measured in Alagoas.Database of air pollutants of the state of Alagoas.Significant difference in the concentration of air pollutants between the dry and rainy seasons.Correlation between air pollutantsSpatio-temporal variability of the airborne pollutant criteria measured in Alagoas.Database of air pollutants of the state of Alagoas.Significant difference in the concentration of air pollutants between the dry and rainy seasons.Correlation between air pollutants [ABSTRACT FROM AUTHOR]

Peroxyacetyl nitrate (PAN) is an important photochemical product and affects ozone (O3) formation in the troposphere. Yet, the long-term observation of PAN remains scarce, limiting the full understanding of its impacts on photochemical pollution. Here, we observed PAN from 2018 to 2022 in urban Fuzhou, Southeastern China. We found that, in contrast to upward trend of O3, PAN concentrations shown a significant decreasing trend at an average rate of −0.07 ppb/year. NO2, CO, UVB, and T contributed to the decreasing trend of PAN according to Machine learning analyses, while the effect of O3-represented atmospheric oxidation capacity on PAN was fluctuating from year to year. Chemical box model revealed active PA production and depletion in Fuzhou. Thus, despite the decreasing PAN concentration, PAN chemistry effectively promoted O3 formation by rising ROx levels, leading to increases of 2.18%–58.4% in net O3 production rate in different years. Our results provide valuable insights into the evolution of photochemical pollution in urban environments. [ABSTRACT FROM AUTHOR]

Quantifying the variable impacts of wildfire smoke on ozone air quality is challenging. Here we use airborne measurements from the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) to parameterize emissions of reactive nitrogen (NOy) from wildfires into peroxyacetyl nitrate (PAN; 37%), NO3− (27%), and NO (36%) in a global chemistry‐climate model with 13 km spatial resolution over the contiguous US. The NOy partitioning, compared with emitting all NOy as NO, reduces model ozone bias in near‐fire smoke plumes sampled by the aircraft and enhances ozone downwind by 5–10 ppbv when Canadian smoke plumes travel to Washington, Utah, Colorado, and Texas. Using multi‐platform observations, we identify the smoke‐influenced days with daily maximum 8‐hr average (MDA8) ozone of 70–88 ppbv in Kennewick, Salt Lake City, Denver and Dallas. On these days, wildfire smoke enhanced MDA8 ozone by 5–25 ppbv, through ozone produced remotely during plume transport and locally via interactions of smoke plume with urban emissions. Plain Language Summary: Wildfires have torn across western North America over the last decade. Smoke from wildland fires in Canada can travel thousands of kilometers to US cities and reacts with urban pollution to create harmful ozone, a criteria pollutant regulated by the US Environmental Protection Agency. Accurately quantifying this impact is needed to inform US air quality policy, but is challenging due to complex physical and chemical processes. In this study, we analyze surface and airborne measurements, alongside a new variable‐resolution global chemistry‐climate model, to better understand these processes. We show that the near‐field conversion of nitrogen oxide (NOx) emissions from wildfires to peroxyacetyl nitrate (PAN) and other more oxidized forms reduces their localized impacts on ozone. PAN is the principal tropospheric reservoir for NOx radicals. When aged smoke plumes descend southward from Canada toward US cities, higher temperatures cause PAN to decompose and thus help production of ozone during smoke transport. On days when the observed ozone levels exceed the air quality limit (70 ppbv for 8‐hr average), wildfire smoke can contribute 5–25 ppbv. Key Points: Sequestration of wildfire NOx emissions in Canada as peroxyacetyl nitrate (PAN) enhances the downwind impacts on US O3 air qualityPyrogenic volatile organic compounds and PAN decomposition increase the contribution of aged Canadian smoke plumes to O3 in US citiesAccounting for these effects in a high‐resolution chemistry‐climate model improves simulation of smoke‐impacted high‐O3 events in US cities [ABSTRACT FROM AUTHOR]

Coppe and zinc are priority pollutants in city soils. Copper and zinc are the limiting factors for lawn grasses. Cell selection can increase the resistance of lawn grasses to zinc and copper. The effect of zinc on the morphogenic ability of the callus was determined. The results of this study showed that zinc is less toxic to calli than copper. The method of obtaining lawn grass resistant to zinc has been developed. The results were used to develop the cell selection technology for obtaining plants resistant to the complex effect of zinc and copper. Concentrations of Copper (75 mg/l) and zinc (150 mg/L) were selected as selective. The author developed the cell selection scheme for obtaining plants resistant to the complex effect of Cu and Zn. The regenerants showed increased resistance to copper and zinc. [ABSTRACT FROM AUTHOR]

This paper analyses the intertwined impacts of the 2018 US sanctions on Iran and the COVID-19 pandemic (as examples of unplanned international conflicts and global crises) on the source and extent of air pollution in Tehran, the capital of Iran. The impacts are parametrized using the levels of criteria air pollutants (CAP) for 5 years (2015–2020), which were previously deweathered using the promising machine learning technique of Random Forest (RF). The absolute principal component scores-multiple linear regression (APCS-MLR) method and the bivariate polar plot (BPP) technique are used here to analyze the source apportionment profile of the city for the business as usual (BAU; 2015 to 2018), sanctions (2019), and COVID-19 and sanctions (2020) intervals. The results show the severe impact of the 2018 US sanctions on Tehran's air quality (AQ); O3, NO2, CO, PM2.5, and PM10 levels increased by 117%, 55%, 20%, 35%, and 10%, respectively, while SO2 levels decreased by 30%. The sanctions also triggered a number of events, such as the disruption of the high-grade fuel supply chain and the Mazut crisis, which directly or indirectly accelerated the photochemical production of local tropospheric ozone to some extent. Sanctions also disrupted Tehran's AQ response to the pandemic, with CAP levels decreasing by only 2–7% during the pandemic. The ozone and PM10 BPPs show that the source apportionment profile of the city is dominated by local anthropogenic emission sources, especially urban transport, after the sanctions and the pandemic. Results also show that the impact of soft wars, such as the US sanctions against Iran, on urban air quality degradation is much stronger than that of hard wars, such as the Russia-Ukraine war. [ABSTRACT FROM AUTHOR]

Neonicotinoids (NEOs), the most widely used class of insecticides, are pervasive in the environment, eliciting concerns due to their hydrophilicity, persistence, and potential ecological risks. As the leading pesticide consumer, China shows significant regional disparities in NEO contamination. This review explores NEO distribution, sources, and toxic risks across China. The primary NEO pollutants identified in environmental samples include imidacloprid, thiamethoxam, and acetamiprid. In the north, corn cultivation represents the principal source of NEOs during wet seasons, while rice dominates in the south year-round. The high concentration levels of NEOs have been detected in the aquatic environment in the southern regions (130.25 ng/L), the urban river Sects. (157.66 ng/L), and the downstream sections of the Yangtze River (58.9 ng/L), indicating that climate conditions and urban pollution emissions are important drivers of water pollution. Neonicotinoids were detected at higher levels in agricultural soils compared to other soil types, with southern agricultural areas showing higher concentrations (average 27.21 ng/g) than northern regions (average 12.77 ng/g). Atmospheric NEO levels were lower, with the highest concentration at 1560 pg/m3. The levels of total neonicotinoid pesticides in aquatic environments across China predominantly exceed the chronic toxicity ecological threshold of 35 ng/L, particularly in the regions of Beijing and the Qilu Lake Basin, where they likely exceed the acute toxicity ecological threshold of 200 ng/L. In the future, efforts should focus on neonicotinoid distribution in agriculturally developed regions of Southwest China, while also emphasizing their usage in urban greening and household settings. [ABSTRACT FROM AUTHOR]

Noise in large urban areas, which is mainly generated by road traffic and by the human activities carried out nearby and inside the area under study, is a relevant problem. The continuous exposure to high noise levels, in fact, can lead to several problems, largely documented in the scientific literature. The analysis and forecasting of the noise level in a given area are, then, fundamental for control and prevention, especially when field measurements present peculiar trends and slopes, which can be modeled with a Time Series Analysis approach. In this paper, a hybrid model is presented for the analysis and the forecasting of noise time series in urban areas: this technique is based on the application of a deterministic decomposition model followed in cascade by a predictor of the forecasting errors based on an artificial neural network. Two variants of the hybrid model have been implemented and presented. The time series used to calibrate and validate the model is composed of sound pressure level measurements detected on a busy road near the commercial port of an Italian city. The proposed hybrid model has been calibrated on a part of the entire time series and validated on the remaining part. Residuals and error analysis, together with a detailed statistical description of the simulated noise levels and error metrics describe in detail the method's performances and its limitations. [ABSTRACT FROM AUTHOR]

This research aims to assess trace elements of contamination by agricultural soils in the Al-Haye district. Soil samples were collected from a selected agricultural area near the banks of the Tigris River, and trace elements (Ag, As, Ba, Cd, Co, CR, Cu, Fe, Hg, Mn, Ni, Pb, Se, V, Zn, Zr, Pb, Se, V, Zn, Zr), pH, electrical conductivity, and organic matter were identified in soil samples. The pH of the soil sample ranged between 7.7 and 7.6, which is equivalent to the pH of the sub-alkalis (7.3). The organic matter content is 1.8433%; this range of organic matter is between 1.56 and 1.98. The average soil conductivity was 995.37 ug/cm. The level of trace contamination was found in soil samples as follows: Fe> Mn> Ba> Cr> Ni> Zr > V > Zn > Cu> Pb> Co> Ag >Cd> Hg> Se. Soil samples contained concentrations of Cd, Cr, Cu, Mn, and Ni much higher than the global average of unpolluted soil concentrations. In contrast, only half of the zinc samples exceeded the calculated average global average of the unpolluted soil, and lead had values within the international level of the unpolluted soil. The study area needs an environmental management system to manage and treat soil pollution in urban areas. [ABSTRACT FROM AUTHOR]

Diesel pallet trucks, a type of heavy-duty diesel trucks (HDDTs), have historically been a vital component in logistics and transport due to their high payload capacity. However, they also present significant challenges, particularly in terms of emissions which contribute substantially to urban air pollution. Traditional HDDTs emission measurement methods, such as engine bench tests and those used in laboratory settings, often fail to capture real-world emission behaviors accurately. This study specifically examines the real-world emission characteristics of diesel pallet trucks exceeding 30 t under varying loads (unloaded, half loaded, and fully loaded) and different road conditions (urban, suburban, and high-speed). Considering that data quality is the key to the accuracy of the scheme, this research utilized a portable emission measurement system (PEMS) to capture real-time emissions data of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOX), and total hydrocarbons (THC). Key findings demonstrate a direct correlation between vehicle load and emission factors, with the emission factors for CO2, CO, and NOX increasing by 39.5%, 105.4%, and 22.7%, respectively, from unloaded to fully loaded states under comprehensive operating conditions. Regression analyses further provide an emission factor prediction model for HDDPTs, underscoring the continuous relationship between speed, load, and emission rates. These findings provide a scientific basis for pollution control strategies for diesel trucks. [ABSTRACT FROM AUTHOR]

The impact of heavy fuel oil (HFO) on the chemical and isotopic composition of submicron particulate matter (PM1) was investigated. For this purpose, we conducted an analysis of water-soluble inorganic ions (WSIIs) and multiple isotopes (δ34S, δ13C, 14C) of PM1 and SO2 collected during two heating periods: before (2021–2022) and during the use of HFO (2022–2023) in Vilnius, Lithuania. The results showed that the combustion of HFO increased the concentrations of SO2 (by 94%) and PM1-related sulfate (by 30%). It also altered the chemical composition of PM1, with sulfate becoming the predominant component (~40%) of WSIIs. The stable sulfur isotope ratios of SO2 (δ34SSO2) and sulfate (δ34SPM1) shifted significantly to more negative values (δ34SSO2 = 0.4‰, δ34SPM1 = −0.3‰) compared to the previous heating period. Anticorrelation between δ13C and δ34S values indicated increased contributions of 13C-enriched fossil fuel sources (coal and HFO) in EC, although the share of fossil fuels in elemental carbon (EC) slightly decreased during the HFO period. The combustion of HFO affected the concentrations of PM1 chemical components and substantially impacted the isotopic composition and source contributions of sulfate and EC. [ABSTRACT FROM AUTHOR]