Water pollution in Iraq has been extended disaster edge; this pollution is caused by wastes and sewages into soil and rivers, pollutant water sources influence the outbreak and serious epidemic status among the population.. The aim of this study is to determine the bacteriological quality of drinking water sources and characteristics of water-borne diseases especially diarrheal cases in Darbandikhan city. 166 water samples, collected from the different sources and areas, were tested for the presences of coliform bacteria as an indicator for pathogen contamination. Most probable number index was used for coliform enumeration. 161 diarrheal cases were taken as a sample from the patients were admitted to the general hospital in Darbandikhan district.. The questionnaire form was planned to view characteristics of diarrheal cases and patients were interviewed directly, the data was analyzed by STATA software application. 46% of the diarrheal cases used tap water for drinking. On the other hand, the reminder (54%) used other sources for the same purpose. All the risk factor such as type of water source, sufficiency of the water, duration of water storage and chlorination were associated with diarrhea. Almost half of the cases were children and three quarters were single. The data was analyzed by STATA version 13.1.This study indicated that the majority of drinking water sources in Darbandikhan city are not suitable for drinking, although net pipe system supplied chlorine significantly it has been proven that the tap water from the homes is not suitable for consumption.

The coronavirus disease (COVID-19) pandemic caused by spreading rapidly a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has imposed a unique situation for the humanity. Sao Paulo has reported 124,105 confirmed cases of COVID-19 and 5,623 deaths up to June 14th, being considered the epicenter of the pandemic in Brazil and in South America. Due to the measures for social distancing, there was a drop in the air pollution concentration in Sao Paulo. Starting on March 16th, 2020, we broke 90 days of social distancing into 13 weeks and compared to an equivalent period in 2019. We investigated the air quality improvement during the quarantine period and compared the associated avoided deaths to COVID-19 burden deaths. Nitrogen dioxide (NO₂) was the best indicator of air quality in the analyzed weeks, since its reduction reached 58 %. Our study showed that the 5,623 deaths occurred during the analyzed weeks of quarantine represents an economic health loss of US$ 10.5 billion. In opposite, we observed a significant air quality improvement due to pollutants concentrations’ reductions during the analyzed weeks. Considering PM₁₀, PM_2.5 and NO₂, the decrease of concentration levels respectively avoided 78, 337 and 387 premature deaths and prevented up to US$ 1.5 billion on health costs. These results highlight the importance of continuing to enforce existing air pollution regulations and measures to protect human health both during and after COVID-19 pandemic.

Keenjhar Lake is the main source of drinking water for the metropolitan city of Karachi. The release of untreated wastewater from Kotri industrial area and other sources have made the lake water polluted. This study was subjected to determine the impacts of such pollutant sources on the water quality of Keenjhar Lake. The study involves the analysis of water quality parameters of Keenjhar Lake and its Feeding source (KB Feeder). The sampling sites were selected based on the sources of contamination. The water samples are tested for physical, chemical and microbiological parameters. The result of water analysis indicates the contamination level of the lake is quite alarming for the sites of Kotri effluent and WAPDA colony where Total Dissolved Solids (TDS), Chloride and other ionic metals were quite higher in concentration than other sites. These sites are also contaminated with Fluoride and Arsenic which are carcinogenic elements. The study reveals that the contamination level of feeding source is causing big non-reversible damage to the lake if continued to be uncontrolled. This contamination is mainly due to the release of toxic metals and ions in the KB feeder caused by human carelessness.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.

Shanghai is experiencing water supply problems caused by heavy pollution of its raw water supply, deficiencies in its treatment processes and water quality deteoriation in the distribution system. However, little attention has been paid these problems of water quality in raw water, water treatment and household drinking water. Based on water quality data we show that the raw water sources of the Huangpu River and the Changjiang (Yangtze River) estuary are polluted by microbes (TBC), eutrophication (TP, TN and NH3-N), heavy metals (Fe, Mn and Hg) and organic contamination (chemical oxygen demand [COD], detergent and volatile phenols [VP]). The average concentrations of these contaminants in the Huangpu River are almost double that of the Changjiang estuary forcing a rapid shift to the Changjiang estuary for raw water. In spite of filtering and treatment, TN, NH3-N, Fe, COD and chlorine maxima of the treated water and drinking water still exceed the Chinese National Standard (GB5749). We determine that the relevant threats from water source to household water in Shanghai are: 1) eutrophication arising from highly concentrated TN, TP, COD and algal density in the raw water; 2) increasing salinity in the river estuary, especially at the Qingcaosha Reservoir (currently the major freshwater source for Shanghai); 3) more than 50% of organic constituents and by-products remain in treated water; 4) bacteria and turbidity increase in the course of water delivery to users. The analysis presents an holistic assessment of the water quality threats to metropolitan Shanghai in relation to the city’s rapid development.

Despite increased awareness of and attention to the need for sustainable agriculture, fertilizers and compost application in excess of crop requirements remain common agricultural practices in South Korea, causing eutrophication of freshwater and coastal ecosystems. In this study, a phosphorus (P) budget was developed to quantify P inputs, outputs, and retention in a forested- agricultural watershed. The P budget showed that chemical fertilizers and organic compost were the largest source of P (97.6% of the total) followed by atmospheric deposition (2.1% of the total P), whereas forest export (0.2% of the total) and sewage treatment plants (STPs) (0.1% of the total) were negligible. The dominant P outputs were crop harvesting and hydrologic export to surface water. The P balance showed a significant accumulation of P in the watershed; approximately 87% of the total P input was retained in the soils within the watershed. However, P concentrations in drainage water were still high enough to cause eutrophication of downstream reservoirs. The results provide useful information on the proportion of P export and retention in soils and will help support efforts to improve water quality and design better management of agricultural non-point source pollution.

With the growing size and use of night lights time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night lights data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g. airports, prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20% of the mean. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances, and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.

Abstract: The air pollution dispersion modelling via spatial analyses (Land Use Regression – LUR) is an alternative approach to the air quality assessment to the standard air pollution dispersion modelling techniques. Its advantages are mainly much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate other factors affecting pollutant’s concentration. The goal of the study was to model the PM10 particles dispersion modelling via spatial analyses v in Czech-Polish border area of Upper Silesian industrial agglomeration and compare results with results of the standard Gaussian dispersion model SYMOS’97. Results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover and were included into the LUR model, the LUR model results were significantly improved (65% determination coefficient) to the level comparable with Gaussian model. The hybrid approach combining the Gaussian model with the LUR gives superior quality of results (65% determination coefficient).

It is currently difficult to obtain accurate fine dust information in residential areas due to the insufficient number of air quality monitoring systems and spatial imbalances. Therefore, a detailed particulate matter dispersion model including factors such as land use and meteorological information was developed in this study and used to create fine dust concentration distribution maps. The fine dust concentration distribution maps currently available to citizens were compared with those obtained by dispersion modeling, and population distribution data were employed to compare the populations exposed to fine dust according to the two methods. The results of the existing method and the developed particulate matter dispersion model differed significantly. For instance, the PM2.5 concentrations in Daejeon, South Korea, on February 17, 2018, were 56% “Good” and 44% “Moderate,” according to the existing method, while they were 31% “Good,” 26% “Moderate,” 28% “Unhealthy,” and 15% “Very Unhealthy,” according to the dispersion model. Furthermore, the existing method indicated that no portion of the population was exposed to poor fine dust concentrations, while the proposed model revealed that over 170 thousand people were exposed to such concentrations. These results on fine dust distributions will contribute to sustainable urban and environmental planning.

Environmental legislation is moving towards global standards for ease of application and to impose sanctions and penalties when necessary, without compromising human health and biota. International environmental measures for control and monitoring of atmospheric air only monitor emissions of SO_x, NO_x, O₃, and Pb. In general, most research work in air pollution done using the analysis of elements in rainwater show analysis of trace metals such as Na, Mg, Zn, and Mn. In this work, trace metals in the rainwater at the city of Goiânia, capital of the State of Goiás, were analyzed. Goiânia is a large city set in a predominantly agricultural province located in central Brazil. Presence of trace metals in rainwater was detected, indicating atmospheric air pollution levels higher than occupational limits set by WHO.

Air pollutants such as volatile organic compounds (VOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), as well as water pollutants including heavy metal, are harmful to human and environment. Effective control and reduction of their pollution is therefore an important topic for today’s scientists. Fly ash (FA) is a type of industrial waste that can cause multiple environmental problems if discharged into the air. On the other hand, because of its high porosity, large specific surface area, and other unique characteristics, the FA can also be used as a low-cost and high efficient adsorbent with some simple modifications. This paper reviews the effects of FA on treatment of the above air and water pollution based on our research experience over many years, including to the current status of global FA utilization, physicochemical properties, principle of adsorption, and the application direction of FA in the future. It focuses on the use of nanocomposite technology to fabricate functional FA fibrous membranes to adsorb VOCs from air, and treat heavy metal wastewater. This present review first describes the fabrication technology of FA nanocomposites and their mechanism of adsorption VOCs from air. Utilization of nanofiber technology to fabricate multi-functional FA emerging composite materials to mitigate air and water pollution has great potential in the future, especially use of pollutant material to control other pollutants.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.

The main objective of the present study was to investigate arsenate [As (V)] resistance genes in rice cultivars grown in arsenic contaminated Egyptian soil in order to genetically induce resistance against arsenic in the local rice varieties as well as defining contaminated rice grains and/or soil. Three local rice cultivars; Sakha 102-104 were cultivated on modified Murashige and Skoog Basal Medium (MS medium) containing elevated concentrations of arsenate (0.1, 1 and 10 mg/l). The three varieties showed different resistant attitudes against arsenate with Sakha 104 being the most resistant. Extracted messenger RNA (mRNA) from treated and untreated Sakha 104 plantlets was scanned using differential display to demonstrate the arsenate resistant genes using three different arbitrary primers. About 100 different RNAs with (1500 bp - 50 bp) were obtained from which seven were up-regulated genes, subjected to DNA cloning using TOPO TA system and the selected clones were sequenced. The sequence analysis described four genes out of the seven namely disease resistance protein RPM1, Epstein-Barr virus EBNA-1-like, CwfJ family protein and outer membrane lipoprotein OmlA while the other three genes were hypothetical proteins. It is concluded the four induced genes in the resistant rice cultivar considered as a direct response to arsenic soil pollution. Genes detected in the present study can be used as geno-sensors for rice grains and soil contamination with As (V). Moreover, local rice cultivars may be genetically modified with such genes to induce high resistance and to overcome arsenic soil pollution.

A case-crossover study examined how PM_2.5 from Asian Dust Storms (ADS) affects the number of emergency room (ER) admissions for cardiovascular diseases (CVDs) and respiratory diseases (RDs). Our data indicated that PM_2.5 concentration from ADS was highly correlated with ER visits for CVDs and RDs. The odds ratios (OR) increased by 2.92 (95% CI: 1.22-5.08) and 1.86 (95% CI: 1.30-2.91) per increase 10 µg/m³ in PM_2.5 levels, for CVDs and RDs, respectively. A 10 µg/m³ increase in PM_2.5 from ADSs was significantly associated with increase in ER visits for CVDs among those 65 years of age and older (an increase of 2.77 in OR) and for females (an increase of 3.09 in OR). In contrast, PM_2.5 levels had a significant impact on RD ER visits among those under 65 years of age (OR=1.77). The risk of ER visits for CVDs increased on the day when the ADS occurred in Taiwan and the day after (lag 0 and lag 1); the corresponding risk increase for RDs only increased on the fifth day after the ADS (lag 5). In Taiwan’s late winter and spring, the severity of ER visits for CVDs and RDs increases. Environmental protection agencies should employ an early warning system for ADS to reduce high-risk groups’ exposure to PM_2.5.

This study examines the significant impact of Houthi insurgent activities on maritime traffic within the strategic Red Sea and Suez Canal routes, essential conduits for global trade. It explores the correlation between regional instability, exemplified by Houthi actions from November 19, 2023, to February 5, 2024, and changes in maritime traffic patterns and operational efficiency. This study seeks to answer a critical question in transport geography: How does regional instability, exemplified by Houthi insurgent activities, affect maritime traffic patterns and the operational efficiency of the Red Sea and Suez Canal? Using descriptive statistics, qualitative analysis, and geospatial methods, the research highlights recent trends in maritime traffic and incidents, revealing spatial and geopolitical challenges in this crucial trade route.Findings indicate a notable decline in maritime activity in the Gulf of Aden and Suez Canal due to security concerns from Houthi attacks, prompting a significant shift to alternative routes, particularly around the Cape of Good Hope. This shift underscores the broader implications of regional instability on global trade and the importance of maintaining uninterrupted maritime flow. The study also emphasizes the economic ramifications, such as increased operational costs and freight rates due to longer transit times and enhanced security measures.The research concludes with a call for improved maritime security protocols and international cooperation to protect these strategic maritime pathways. It contributes to the discourse on transport geography by quantifying the direct impacts of regional conflicts on maritime logistics and proposing strategies for future resilience, highlighting the interconnected nature of global trade and security and the need for collective action against evolving geopolitical challenges.

The effects of toxic air in the form of air pollution are known to harm women’s health. New data has shown that air pollution has effects on maternal anemia. Yet the effects of particulate matter 2.5 (PM_2.5) on hemoglobin among reproductive maternal (15-49 years) has been understudied. In this population-based study, we study the region-specific associations between prevalence of hemoglobin among reproductive women and PM_2.5 in 43 countries of Africa from 2000-2019. Using generalized linear regression models, we found that after adjusting for key covariates, PM_2.5 had a slight negative association with hemoglobin among reproductive women. Other studies are needed in other low-income settings to expand our findings.

Research interest in the occurrence, distribution, fate, and toxicity of N-(1,3-Dimethylbutyl)-N’-phenyl-p-phenylenediamine (6PPD) quinone, a derivative of the tire amino antioxidant 6PPD in urban environments, has surged. While several studies have found that 6PPD quinone exhibits acute, reproductive, and behavioral toxicity as well as mutagenicity and hepatotoxicity in aquatic and terrestrial animals, its environmental exposure data are fragmented and lack coherence across the source-to-exposure continuum, making it difficult to use for risk assessment and regulatory purposes. The present work developed an aggregate exposure pathway (AEP) framework to integrate the exposure data. An AEP network was developed for the atmospheric deposition of 6PPD quinone from tire wear in the Pearl River Delta, which led to human exposure. The 6PPD quinone research was organized, visualized, and evaluated with pertinent knowledge gaps identified using the weight of evidence assessment. Eight key exposure states were identified, with only two having high confidence levels and three having low confidence levels. Empirical support for the key transitional relationships decreased from High to Low from the source to the target site, indicating an urgent need for downstream mechanistic data. The proposed AEP framework integrated diverse 6PPD quinone research, facilitating a mechanistic understanding of the source-to-outcome continuum, as well as the development of quantitative predictive models for future research and environmental regulation.

Anthropogenic lighting elicits positive phototaxis responses (i.e., attraction) in birds, insects, and many other species across ecosystems. Impacts from lights in marine systems are poorly understood, despite evidence that vessel lighting can cause seabird disorientation and collisions, potentially leading to injury or mortality. The level of attraction generated by different types of lighting, including light-emitting diodes (LEDs), is also not well understood in most seabirds. Using fairy prions (Pachyptila turtur), a species showing strong positive phototaxis particularly to artificial lights on vessels, we investigated the effects of LED colour and lumen output at a colony during the breeding season. We used six random treatment groups (control (dark), red light, amber low lumen, amber high lumen, white low lumen, and white high lumen) and measured attraction and disorientation. Data was analysed using generalised linear mixed-effects models while accounting for environmental variables. Results showed that the control (“dark”) and red light attracted fewest birds, and attraction/disorientation did not differ between these. Medium responses were elicited by amber low/high and white low, while white high lumen induced the highest abundance and attraction/disorientation response. These results agreed with our desktop study, which predicted response rankings based on each light treatment’s colour spectrum and lumen output and a related species’ spectral response. Furthermore, time of night increased bird counts, as did higher humidity, increased moon illumination, and reduced moon visibility. Our data highlight the need to consider LED colour, lumen output, and time of night to reduce anthropogenic lighting impacts on land and at sea.

An online survey assessed the awareness of Nelson region’s residents, comparing responses between those who experienced the installation and those who did not. Findings indicated that eco-art installations can significantly enhance public understanding of ALAN's environmental and health impacts. The installation successfully increased specific knowledge about ALAN, with 92% of visitors reporting learning something new, however overarching knowledge and levels of concern were largely similar between the groups. Emotional engagement was high, with 62% of viewers stating that the installation invoked an emotional response. While the study did not measure behavioural changes, 94% of festival participants found it at least ‘somewhat appropriate’ and 64% ‘very’ or ‘entirely appropriate’ to raise awareness of these issues at such events, suggesting a potential foundation for future action. This research underscores the promise of art-science collaborations in environmental education and public engagement.

More than 400 million tons of livestock waste are generated annually by approximately 25,000 concentrated animal feeding operations (CAFOs) located in the United States (US). These operations give rise to externalities, including adverse local and global health impacts from CAFO waste emissions, which can potentially outweigh their economic viability. However, a shortage of evidence synthesis research on US-based CAFO emissions may hinder effective policy development. This scoping review (ScR) study, conducted following guidance from the Joanna Briggs Institute, searched databases including Scopus, Web of Science, PubMed and Embase in May 2020, yielding ten publications meeting inclusion criteria. Results suggest possible CAFO worker exposures to multidrug-resistant Staphylococcus aureus (MDRSA), campylobacteriosis and cryptosporidiosis. Communities near CAFOs experienced higher rates of adverse health impacts compared to those in non-CAFO areas, with patterns suggesting proximity may correlate with increased odds of detrimental health effects. Implicit global health threats include Methicillin-resistant Staphylococcus aureus  (MRSA), MDRSA, campylobacteriosis, tuberculosis, and cryptosporidiosis. These studies provide foundational insights into CAFO proximity, density patterns, and adverse public health effects, indicating a need for evidence-informed environmental health policies to minimize local and global risks.

Creating accurate emission models capable of capturing the variability and dynamics of modern propulsion systems is crucial for future mobility planning. This paper presents a methodology for creating THC and NOx emission models for vehicles equipped with start-stop technology. A key aspect of this endeavor is to find techniques that accurately replicate the engine stop stages when there are no emissions. To this end, several machine learning techniques were tested using the Python programming language. Random forest and gradient boosting methods demonstrated the best predictive capabilities for THC and NOx emissions, achieving R2 scores of approximately 0.9 for both cold and hot engine emissions. Additionally, recommendations for effective modeling of such emissions from vehicles are presented in the paper.

This work aimed to study the effect of repeated exposure to low doses of ozone on alpha-synuclein and the inflammatory response in the substantia nigra, jejunum, and colon. Seventy-two male Wistar rats were divided into six groups. Each group received one of the following treatments: The control group was exposed to air. Ozone groups were exposed for 7, 15, 30, 60, and 90 days for 0.25 ppm. for four hours daily. Afterward, they were anesthetized, and their tissues were extracted and processed using western blotting, immunohistochemistry, and qPCR. The results indicate a significant increase in alpha-synuclein in the substantia nigra and jejunum from 7 to 60 days of exposure, an increase in NFκB from 7 to 90 days in the substantia nigra, while in the jejunum, a significant increase is observed at 7 and 15 days and a decrease at 60 and 90 days for the colon. Interleukin IL-17 shows an increase at 90 days in the substantia nigra in the jejunum and increases at 30 days and in the colon at 15 and 90 days. Exposure to ozone increases the presence of al-pha-synuclein and the loss of regulation of the inflammatory response, which contributes significantly to degenerative processes.

Objectives: Recently, desert dust in Europe has been recognized as a cardiovascular health problem. In Spain, desert dust inflows in recent years have been associated with worsening air quality. The present study examines whether desert dust events are related to the incidence of acute coronary syndrome (ACS) in patients under 55 years of age. Methods: Data from 2416 consecutive patients admitted to a tertiary hospital due to ACS were prospectively analyzed. A case-crossover time-stratified design using Poisson conditional regression models was applied to estimate the impact of desert dust events involving particulate matter concentrations of aerodynamic diameter < 10 μm (PM10) on the incidence of ACS. Results: Desert dust intrusion on days 0 to 5 after ACS onset showed no significant association with the incidence of ACS in patients under 55 years of age. The incidence rate ratios of PM10 concentrations 1, 2, 3, 3, 4 and 5 days before ACS onset (for changes of 10 µg/m3) were 1.02 (95% CI 0.97-1.1; p = 0.41), 1.01 (95% CI 0.96-1.07; p = 0.66), 0.99 (95% CI 0.94-1.05; p = 0.78), 0.96 (95% CI 0.9-1.02; p = 0.18) and 0.97 (95% CI 0.91-1.04; p = 0.41). Conclusions: Our findings suggest that desert dust is unlikely to be related to the incidence of premature coronary heart disease.

In recent years, nocturnal ozone enhancement(NOE) events have become a hot research topic in the field of atmospheric environment. By using statistically-based data analysis, we made a comparative investigation about nocturnal ozone concentrations and NOE events in 2022 and 2023, and further explored the effects of NOE events on O3 and PM2.5 at the night of the same day and the next day. The results showed that from 2022 to 2023 in Dongying, the annual average nocturnal ozone concentrations increased from 51 μg/m3 to 59 μg/m3, and the frequency of NOE events was higher in spring, summer and autumn, and lower in winter. NOE events not only had an obvious promoting effect on nocturnal O3 and Ox, and the daily maximum 8 h average concentration of O3 (MDA8-O3) of the same day (more apparent in summer and autumn), and nocturnal PM2.5 and PM2.5-bounded NO3- and SO42- (more apparent in winter), but also had a distinct influence on O3, Ox and MDA8-O3 of the next day (more apparent in summer). The results could strengthen the understanding of the phenomena of NOE events, and provide a scientific basis for the collaborative control of PM2.5 and ozone in urban areas in the Yellow River Delta, China.

Mozambique is one of the poorest countries of the world. However, it has natural resources and if they are managed under sustainable development principles, Mozambique can overcome the current problems. In the present socio-economic status, soil is one of its most important resources and must be protected from pollution and from degradation. This review focuses on the identification and discussion of the main soil quality stressors, namely: soil fertility; deforestation and its sources: agriculture, timber harvesting, charcoal production and uncontrolled fires; mining activities, manly gold artisanal explorations and industrial open-pit coal mining. The sustainable use of the natural resources is mandatory to allow future generations to continue profiting for this nature-based wealth.

The state of Veracruz has ample water resources. However, due to population and industrial growth, there has been an increase in the discharge of wastewater into surface water bodies. To analyze the water quality in the Bobos River, Veracruz, and its sustainability, researchers collected nine samples from nine different points in the reservoir. They measured various parameters such as temperature, pH, dissolved oxygen, conductivity, total nitrogen, nitrate, chemical oxygen demand, total phosphorus, phosphate, dissolved solids, and fecal coliforms. The results showed that the river's water quality is at risk. The concentration of pollutants such as chemical oxygen demand and fecal coliforms is high. Conductivity values ranged from 0.26 to 3.81 mS. If preventive and corrective measures are not taken, the river's ability to purify pollutants will be severely compromised. This study evaluates the physical, chemical, and microbiological characteristics of the water in Bobos River. It specifically investigates the influence of the nearby citrus industry on the river's water quality. The study also aims to promote environmental sustainability.

In the present work, a study has been carried out on the contamination of heavy metals in urban dust deposited on the roads of the city of Cartagena (Spain), in order to know the content of metals such as Ni, Zn, Pb, Cd, Cr and Cu. Likewise, the possible relationship of the concentration of heavy metals with the color of the sample, level of magnetism and traffic density was studied. Contamination was evaluated using several indices such as contamination factor (CF), enrichment factor (EF), geoacumulation index (Igeo), pollutant load index (PLI) and ecological risk index (RI). A total of 88 samples were taken in the urban area of Cartagena, and the metals were determined by acid digestion and measured by inductively coupled plasma mass spectrometry. The concentration of heavy metals in urban dust from Cartagena was Zn (672 mg/kg) &gt; Cu (248.9 mg/kg) &gt; Pb (227 mg/kg) &gt; Cr (82.7 mg/kg) &gt; Ni (47.7 mg/kg) &gt; Cd (4.1 mg/kg). Contamination levels were high in Pb, Zn, Cd and Cu, according to environmental indices. A correlation was found between magnetism and metal concentration, which was repeated for all metals except Cd. Dark-colored samples contained higher metal concentrations than light-colored samples. Meanwhile, streets with medium and low traffic intensity were found to have higher concentrations of heavy metals. This study's objective was to identify pollution hotspots caused by heavy metals in dust in the urban ecosystem of Cartagena city.

2,4-dichlorophenoxyacetic acid (2,4-D) is a globally used herbicide and is frequently found in water samples. This fact has prompted studies on its effects in non-target organisms, revealing significant alterations on liver structure and function. In this review, we evaluated the literature on the hepatotoxicity of 2,4-D, focusing on morphological damages, biomarkers of toxicity and affected liver functions. Searches were conducted on PubMed, Web of Science and Scopus and 83 articles were selected after curation. Among the studies, 72% used in vivo models and 30% used in vitro models. Additionally, 48% used the active ingredient, and 35% used commercial formu-lations in exposure experiments. The most affected biomarkers were related to a decrease in an-tioxidant capacity, including alterations in the activities of catalase and superoxide dismutase, and in the levels of malondialdehyde. Changes in energy metabolism, lipids, liver function, and xenobiotic metabolism were also identified. Furthermore, we found studies about the effects of 2,4-D in mixtures with other pesticides, as well as hepatoprotection trials. The reviewed data in-dicate that the reduction in antioxidant capacity and oxidative stress play an important role in 2,4-D-induced hepatotoxicity. However, the mechanism of action of the herbicide is still not ful-ly understood and further research in this area is needed.

The aim of the present study, was to evaluate the wild freshwater fish health status using a vast array of biomarkers as predictive factor of pollutant exposure. European eel (Anguilla anguilla) and Brown trout (Salmo trutta fario), resident in rivers with different degree of pollution in the South of Italy (Picentino river with good environmental quality and Tusciano river with low environmental quality), were examined using biometric parameters, histopathological and immunohistochemical biomarkers to evaluate the health status and a possible correlation with the water quality. Several alterations identified in the liver positively correlated with water and soil pollutants were: hemorrhage (P≤0.05), cytoplasmic vacuolization (P≤ 0.01), hemosiderosis (P≤0.05), irregular arrangement of hepatocytes (P≤ 0.01), lipid accumulation (P≤0.05), necrosis (P≤ 0.01), cellular hyperplasia (P≤0.05), leukocyte infiltration (P≤ 0.01) and melanomacrophages centers (MMC) (P≤ 0.01). In the spleen, only hemosiderosis correlated with water and soil pollutants (P≤ 0.05). The inflammatory biomarker tumor necrosis factor α (TNFα) and ciclooxigenase 2 (COX2) responded to the environmental pollution, as well as the oxidative stress biomarkers superoxide dismutase (SOD) and 8-Hydroxy-2'-deoxyguanosine (8-OHdG). Erythrocytic nuclear abnormalities and erythrocytic cellular abnormalities were found significantly higher in the blood of both Europen eel (P&lt;0.0001) and Brown trout (P &lt;0.001) in the Tusciano river with respect to the Picentino river. Taken together, these results outline the need to increase the number of suitable biomarkers to assess fish health and reinforce the importance to employ additional biomarkers in biomonitoring programs which can be applied to evaluate the water quality and environmental risk assessment around the world

The cities of the future are places of sustainable mobility and a continuous reduction in the amount of harmful substances entering the surrounding environment. Current emission models are mainly dedicated to fully combustion vehicles and do not fully reflect the actual emissions of vehicles in the fleet, which is becoming increasingly diverse. The increasing share of hybrid and electric vehicles is generating the need to measure emissions and energy consumption from these vehicles and to develop new emission models that are accurate. This problem mainly concerns low-emission zones in cities, where mobility planning should be based on simulation models that are based on a continuously updated database. This work concerns the proposal of a two-dimensional model of emissions from hybrid vehicles using artificial neural networks for low-emission zones. The results can be used to further develop such emission models.

Recent scholarship highlights the significant environmental impact of the expanding hydraulic fracturing industry, necessitating up-to-date, comprehensive, national-scale assessments. Addressing this gap, this literature review provides a thorough analysis of the contamination and induced seismicity associated with shale-gas hydraulic fracturing in the United States. Employing systematic reviews of literature and federal reports up until July 2023, this study reveals multiple areas of concern. Notably, water and soil contamination, seismic activity, and air pollution are identified as significant challenges linked to shale gas extraction. However, ongoing studies are actively exploring remediation strategies, including advancements in monitoring and treatment technologies, aimed at mitigating the impact of contamination. These findings underscore the need for stringent regulations, continuous research, and effective management practices. This work emphasizes the importance of a collaborative approach that leverages field studies, experimental investigations, and computational advancements to ensure the responsible development of shale gas resources.

Taking Shanxi Province, a typical energy region in China, as the research object, data on economic development quality and environmental pollution intensity from 2001 to 2021 were selected. Linear regression, numerical simulation, and Pearson correlation coefficient were used to analyze the evolution characteristics of economic development quality and environmental pollution intensity in Shanxi Province in the past 20 years, and to explore the relationship between economic development and environmental pollution. The results indicate that since 2001, Shanxi Province has made long-term progress in economic development, with GDP increasing by nearly 10 times and an average annual growth rate of around 7%. In the past 20 years, the main pollutants have shown a trend of increasing first and then decreasing steadily, with a turning point occurring during the "12th Five Year Plan" period. This shows that the environmental policies and investments of the Chinese and Shanxi provincial governments in the past 10 years have been effective in the new era. The numerical simulation curve results show that the per capita GDP exhibits a classic inverted "U" curve relationship with wastewater and SO2 emissions, with a turning point occurring at around 20000 yuan per capita GDP; However, there is a monotonic decreasing trend with Chemical oxygen demand and ammonia nitrogen emissions, and a monotonic increasing trend with solid waste generation. There is no turning point yet. The correlation analysis results further support the fitting curve conclusion.

In this paper, a Markov random field model is proposed to determine a site’s light pollution risk level. The specific data of 12 indicators of five typical cities in China is first collected to establish a hierarchical indicator system using an R-type clustering algorithm. Then, the entropy weight method is used to filter, determine 10-factor indicators, three potential impact indicators, and a light pollution risk index, and establish an undirected probability map model. A light pollution measurement based on Markov random field is obtained, and a location-based light pollution risk assessment index (LBLPRAI) is proposed. LBLPRAI of different types of sites is analyzed, and three possible intervention strategies are proposed to solve the light pollution problem: road lighting system planning, increasing vegetation coverage, and building system planning. Finally, the simulated annealing algorithm is used to determine the best intervention strategy, and it is concluded that the use of strategy 1 in the urban community 2 is the most effective measure, which can reduce the risk level of light pollution by 17.2%.

We provide quantitative results from GIS-based modelling of urban emission functions for a range of representative low- and mid-rise locations, ranging from individual streets to residential communities within cities as well as entire towns and city regions with the aim of whether lantern photometry or built environment has the dominant effect on light pollution. We demonstrate the scalability of our work by providing results for the largest urban area modelled to date, comprising the central 117 km2 area of Dublin City and containing nearly 42,000 public lights. Our results show a general similarity in the shape of the azimuthally-averaged emission function for all areas examined, with differences in total light output distribution depending primarily on the nature of the lighting and, to a smaller extent, on the obscuring environment including seasonal foliage effects. A comparison with global satellite observations shows that they are consistent with the deduced angular emission function for other low-rise areas worldwide. We further validate our approach by comparing results for a range of urban locations by the close agreement observed in a detailed comparison of with calibrated imagery from the International Space Station. To our knowledge, this is the first such detailed quantitative verification of light loss calculations.

The output of non-ferrous metal smelters is 450,000 tons (3.1% of world output), and copper ranks 10th in the world for health impact evaluation. According to the latest information from smelters, the overall average concentration in 2020 was 8.2 ppb each of SO2, NO2, O3, PM10, and PM2.5. 7.5 ppb, 30.8 ppb, 21.3 μg/m3, and 13.2 μg/m3, and the maximum concentrations were 390 ppb, 50 ppb, 167 ppb, 148 μg/m3, and 107 μg/m3. Art Corporation, A2C (Atmosphere to CFD) model was used to investigate the resident health follow-up management (cohort study) study (SAS Enterprise Guide) as the basis for the source of diffuse pollution in the area. The average concentration of PAHs (polynuclear aromatic hydrocarbons) among carcinogens in the air by survey site was the highest in Seokpo 4-ri (60.7 ng/m3), followed by Seokpo 1-ri (48.6 ng/m3) and Seokpo. Among the respiratory diseases, the disease (Acute upper respiratory tract disease(J00-J06), Other upper respiratory tract diseases (J32-J39), Acute lower respiratory tract infection (excluding pneumonia) (J20-J22), Chronic lower respiratory disease (persons) (excluding J40-J47, J45-J46), Asthma (J45-J46), Rhinitis (J30-J31), Respiratory disease (J00-J99), Cough (R05)) that has a correlation between the exposed area and the control area is as follows.

Euglenoids are a common component of primary producers in high acidic and organic shallow freshwater systems. They are free-living photosynthetic motile flagellates exhibiting rapid responses to various external stimuli including chemical pollution. The unique combination of diverse physiological processes of Euglena such as photosynthesis, movement, and orientation offers a range of sensitive criteria that respond to aquatic pollutants. This has led to the development of several acute and chronic assay methods to monitor the adverse impacts of potent toxicants in aquatic ecosystems. Euglenoids also reflect the consequences of physical stress factors such as UV radiation. This review summarizes the ecotoxicity studies using euglenoid flagellates as model species and their potential to contribute toward rapid screening of ecological impacts of pollution in the aquatic environment. Factors determining the reliability of Euglena tests are outlined.

In the article a statistical approach to the assessment of the emission rates discharged by the road traffic in a spatial context is proposed. It exploits an indicator, the Yearly Average Vehicle, representing the pollutant emission rate of the average vehicle belonging to a specific category, and considers the statistical variability of most of the involved traffic parameters: vehicle speed and mileage travelled in the considered time period. Finally, indicators, assessing both the most probable value among the possible emission rates and the extent of their variability range, are proposed. They may also be used to underpin decision making-processes, when the effects of different policies addressing air pollution issues, are to be evaluated. Therefore, they are suitable for the analysis supporting urban planning activities, with a view to addressing and mitigating the effects and the consequences of pollution due to the transportation sector of the urban context.

Recent work on heavy metal pollution in Manila Bay suggests elevated concentration in the surface sediments. It is critical to identify the sources of these heavy metals to effectively rehabilitate the bay. Our study investigated the sources of the heavy metal pollution that ended up in Manila Bay and the risks associated with these toxic metals based on a recent survey conducted. Surface sediment samples with higher heavy metal concentrations were found in the upper to middle parts of the bay while lower concentrations were in the southeast areas. Multivariate analyses such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and Pearson correlation analysis were used to identify the sources of the heavy metals. The heavy metal pollution in Manila Bay is attributed to several rivers draining northeast of Manila Bay, particularly the Marilao-Meycauayan-Obando River System (MMORS) which is cited as one of the 30 dirtiest river systems in the world. The ecological risks associated with heavy metals in the sediments found higher incidences of toxicity in north and middle parts of Manila Bay. Cu and Cr posed the highest risks of toxicities than any other heavy metals. Based on our analysis, the counterclockwise water gyre of the bay can explain the distribution and ecological risks associated with the heavy metals as supported by the findings of the PCA. Given the high priority by the Philippine government to rehabilitate the bay, our study strongly shows that efforts to restore the ecological status of Manila Bay will only succeed if the pollution from major rivers draining to it will be properly addressed.

A complete halt on all anthropogenic activities and human movement due to COVID-19 lockdown has provided a great opportunity to assess the impact of human activities on coastal marine ecosystems. The current study assessed the concentration of the metals in water samples of the largest brackish water lagoon of Asia; the Chilika lagoon in the state of Odisha, India between pre-COVID-19 and post-COVID-19 lockdown scenarios. Monthly water samples (n=30 stations) from 0.3 m depth were collected from three sectors of the lagoon seasonally; pre-monsoon, monsoon, and post-monsoon. In addition to various physical parameters [pH, salinity, alkalinity, (DO) dissolved oxygen, (TDS) total dissolved solids, and (EC) electrical conductivity] the collected water samples were analysed for 18 trace metals (Al, As, Ba, Be, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sr, Th, Tl, U, V). Most of the physical parameters showed a significant variation between pre-and post-COVID-19 scenarios, except for pH and DO. The concentration of five metals (Be, Cd, Co, Ni, and Pb) remained below detection limits in all water samples. The impact of COVID-19 lockdown on the concentration of the metal in the water samples was noticed along with the three sectors of the lagoon. However, eight metals (Al, As, Cr, Fe, Mn, Th, U, and V) were significantly different between the COVID-19 scenarios and the remaining five metals were not statistically significant. The mean concentration of Al, As, Fe, Th, and V were higher in the pre-COVID-19 scenarios, whereas only Cr and Mn were higher in the post-COVID-19 scenarios. The mean concentration of U was similar among both COVID-19 scenarios, even though there were seasonal and sectoral differences. The seasonal influence of riverine influx was more evident on metal concentration during the monsoon season, whereas the difference between sectors was more prominent during the post-monsoon season. An increased number of correlations between physical parameters and metal concentration were observed in the post-monsoon season and post-COVID-19 scenario. This study provides evidence that the imposition of COVID-19 lockdown reduced metal influx in the water column and improved the water quality of the Chilika lagoon. Our results can be used as baseline for metal concentration in surface waters of the lagoon.

The rural communities are affected by gaseous emissions from intensive livestock production. Practical mitigation technologies are needed to minimize emissions from stored manure and improve air quality inside barns. In our previous research, the one-time surficial application of biochar to swine manure significantly reduced emissions of NH3 and phenol. We observed that the mitigation effect decreased with time during the 30-day trials. In this research, we hypothe-sized that bi-weekly reapplication of biochar could improve the mitigation effect on a wider range of odorous compounds using larger scale and longer trials. The objective was to evaluate the effectiveness of biochar dose and reapplication on mitigation of targeted gases (NH3, odor-ous VOCs, odor, GHGs) from stored swine manure on a pilot-scale setup over 8-weeks. The bi-weekly reapplication of the lower biochar dose (2 kg/m2) showed much higher significant percent reductions of emissions for NH3 (33% without & 53% with reapplication) and skatole (42% without & 80% with reapplication), respectively. In addition, the reapplication resulted in the emergence of statistical significance to the mitigation effect for all other targeted VOCs. Spe-cifically, for indole, the % reduction improved from 38% (p=0.47, without reapplication) to 78% (p=0.018, with reapplication). For phenol, the % reduction improved from 28% (p=0.71, without reapplication) to 89% (p=0.005, with reapplication). For p-cresol, the % reduction improved from 31% (p=0.86, without reapplication) to 74% (p=0.028, with reapplication). For 4-ethyl phenol, the percent emissions reduction improved from 66% (p=0.44, without reapplication) to 87% (p=0.007, with reapplication). The one-time 2 kg/m2 and 4 kg/m2 treatments showed similar effectiveness in mitigating all targeted gases, and no statistical difference was found between the dosages. The one-time treatments showed significant % reductions of 33% & 42% and 25% & 48% for NH3 and skatole, respectively. The practical significance is that the higher (one-time) biochar dose may not necessarily result in improved performance over the 8-week manure storage, but the bi-weekly reapplication showed significant improvement in mitigating NH3 and odorous VOCs. The lower dosages and the frequency of reapplication on the larger-scale should be explored to optimize biochar treatment and bring it closer to on-farm trials.

’Lockdown’ periods in response to COVID-19 have provided a unique opportunity to study the impacts of economic activity on environmental pollution (e.g. NO2, aerosols, noise, light). The effects on NO2 and aerosols have been very noticeable and readily demonstrated, but that on light pollution has proven challenging to determine. The main reason for this difficulty is that the primary source of nighttime satellite imagery of the earth is the SNPP-VIIRS/DNB instrument, which acquires data late at night after most human nocturnal activity has already occurred and much associated lighting has been turned off. Here, to analyze the effect of lockdown on urban light emissions, we use ground and satellite data for Granada, Spain, during the COVID-19 induced confinement of the city’s population from March 14 until May 31, 2020. We find a clear decrease in light pollution due both to a decrease in light emissions from the city and to a decrease in anthropogenic aerosol content in the atmosphere which resulted in less light being scattered. A clear correlation between the abundance of PM10 particles and sky brightness is observed, such that the more polluted the atmosphere the brighter the urban night sky. An empirical expression is determined that relates PM10 particle abundance and sky brightness at three different wavelength bands.

There is accumulating evidence that prenatal exposure to air pollution disturbs fetal growth and development, but little is known about these effects in cold climates or their season-specific or joint effects. Our objective was to assess independent and joint effects of prenatal exposure to specific air pollutants on the risk of low birth weight (LBW). We utilized the 2568 children of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo. We conducted stratified analyses for births during warm and cold seasons separately. We analyzed the effect estimates using multi-pollutant Poisson regression models with risk ratio (RR) as the measure of effect. The risk of LBW was related to exposure to CO and (adjusted RR 1.44, 95% CI: 1.04-2.00) and exposure to O3 in the spring-summer season (1.82, 1.11-2.96). There was also evidence of synergistic effects between CO and O3 (relative risk due to interaction, RERI, all year 1.08, 95% CI: 0.27-4.94, spring-summer 3.97, 2.17-25.85) and PM2.5 and O3 (all year 0.72, -0.07-3.60, spring-summer 2.80, 1.36-19.88). We present new evidence of both independent and joint effects of prenatal exposure in a cold climate on the risk of LBW at low levels of air pollution.

Coal-fired thermal plants (CTPP) are known to pollute the atmosphere with emission of many greenhouse gases and particulate matter. The power generation from these thermal plants cannot be stopped completely because it forms the backbone of the grid power supply. It is necessary to study the dispersion patterns of pollutants that affect the health of the people. The dispersion patterns are location specific since they depend on local meteorological conditions. In this study, the dispersion of particulate matter (PM) and sulphur dioxide (SO₂) from a CTPP with 275 m high stack are studied under different atmospheric boundary layer (ABL) of neutral, stable and unstable conditions up to a distance of 30 km from the stack. The plume of the PM spreads under all conditions. During some parts of the day, PM settles around the stack while at other times PM keeps suspending in the air for the full distance under study. Sulphur dioxide dilutes to concentrations below the detection limits in about 12-13 km from the stack for neutral and unstable ABL whereas for the stable ABL, the dispersion is up to 30 km. The 24 h weighted average concentration of sulphur dioxide, at 10 m height from the ground, is 14.2 mg/m³ at a distance of 25 kms from the CTPP, which is comparable with the value of 9.2 mg/m³ measured at the Air Quality Stations located around the same distance. Based on the results policy changes that need to be implemented are suggested.

The rapid development of China's economy has led to a rapid increase in energy production and use. Among them, the excessive consumption of coal in fossil energy consumption is the leading cause of air pollution in China. This paper incorporates renewable energy innovation, fossil energy consumption and air pollution into a unified analysis framework, and uses spatial measurement models to investigate the spatial effects of renewable energy green innovation and fossil energy consumption on air pollution in China, and decomposes the total impact into direct and indirect effects. influences. The empirical results show that China's air pollution, renewable energy green innovation and fossil energy consumption are extremely uneven in geographical space, generally showing the characteristics of high in the east and low in the west, and showing a strong spatial aggregation phenomenon. Fossil energy consumption will lead to increased air pollution, and the replacement of fossil fuels with clean and renewable energy is an important means of controlling pollution emissions. The direct and indirect effects of renewable energy green innovation on air pollution are significantly negative, indicating that renewable energy green innovation not only suppresses local air pollution, but also suppresses air pollution in neighboring areas. The consumption of fossil energy will significantly increase the local air pollution, and the impact on the SO2 and Dust&Smoke pollution in the adjacent area is not very obvious. It is recommended to strengthen investment in renewable energy green innovation, reduce the proportion of traditional fossil energy consumption, and pay attention to the spatial connection and spillover of renewable energy green innovation.

The physical environment plays an important role in the transmission of respiratory infections like Covid-19. To find relevant articles on environmental factors influencing respiratory infection outbreaks, we searched Pub med Central on the following topics: 1. Environmental pollution causing coronavirus fatality- 73 results, relevant 1 article, 2. Environmental factors affecting Covid-19, 149 results from which there were 6 relevant articles, 3. Impact of air pollution on Covid-19 fatality, 10 results, relevant 3 articles, 4. Environmental factors affecting respiratory viruses- 10646 results were obtained, 2 relevant articles. We searched Google scholar on environmental factors affecting Covid-19 transmission and found 7 relevant papers. We excluded the duplicates in each of the key words search. Date of search was on 20^th April 2020. All articles included in results were scrutinized and relevance of articles was based on their content that discussed meteorological and physical environment factors in the spread and severity of Covid-19. We have discussed factors like air pollution, smoking, air temperature, humidity and air velocity as contributing factors. If meteorological factors are conducive to spread in a particular area, we need protective measures way before a respiratory infection outbreak occurs. Covid-19 is a lesson learnt the hard way, and we must enable people to practice hygienic practices with limited resources but high level of protection that it provides. Air pollution control can prevent priming of respiratory system which shall further protect from pulmonary infections.

Heavy metals and organic pollutants are ubiquitous environmental pollutants affecting the quality of soil, water and air. Over the past 5 decades, many strategies have been developed for the remediation of polluted water. Strategies involving aquatic plant use are preferable to conventional methods. In this study, an attempt was made to provide a brief review on recent progresses in research and practical applications of phytoremediation for water resources with the following objectives: (1) to discuss the toxicity of toxic chemicals pollution in water to plant, animals and human health (2) to summarise the physicochemical factors affecting removal of toxic chemicals such as heavy metals and organic contaminants in aqueous solutions by aquatic plants; (3) to summarise and compare the removal rates of heavy metals and organic contaminants in aqueous solutions by diverse aquatic plants; and (4) to summarise chemometric models for testing aquatic plant performance. More than 20 aquatic plants specie have been used extensively while duckweed (L. minor), water hyacinth (Eichhornia crassipes), water lettuce (P. stratiotes) are the most common. Overall, chemometrics for performance assessment reported include: Growth rate (GR), Growth rate inhibition (% Inhibition), Metal uptake (MU), translocation/transfer factor (TF), bioconcentration factor (BCF), Percent metal uptake (% MU), Removal capacity (RC) and Tolerance index (TI) while absorption rate have been studied using the sorption kinetics and isotherms models such as pseudo-first-order (PFO), pseudo-second-order (PSO), Freundlich, Langmuir and Temkin. Using modeling and interpretation of adsorption isotherms for performance assessment is particularly good and increases level of accuracy obtained from adsorption processes of contaminant on plant. Conclusion was drawn by highlighting the gap in knowledge and suggesting key future areas of research for scientists and policymakers.

Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.

Two peat cores from two bogs were used to reconstruct high–resolution changes in atmospheric Pb accumulation rate (Pb AR) in Belgium during the Roman period. The two records were compared to assess the reliability of peat cores as archives of atmospheric Pb deposition and to established histories of atmospheric emissions from anthropogenic sources. To address these issues we analyze Pb concentration and isotopes, using ICP-MS, LA-ICP-MS and MC-ICP-MS in two peat sections, spanning 1000 yr each. Lead concentrations in the two cores range from 0.1 to 60 μg g⁻¹, with the maxima between 15 and 60 μg g⁻¹. The average natural background of Pb AR was 0.005± 0.002 mg m^-2 yr^-1 and the maximum ranges from 0.7 to 1.2 mg m^-2 yr^-1 between 50 BC and AD 215. The highest Pb AR exceed the pre-Roman period values by a factor of 25-30. Pb isotopic composition indicates that mining and metallurgical activities were the predominant sources of pollution during the Roman period. The Pb AR and chronologies in the Belgian peat cores are consistent with those reported for other continental archives as lake sediments, peat and ice cores.

The Atoyac River crosses the metropolitan area of Puebla, Mexico, and presents a condition of severe degradation that has been poorly studied. The research was conducted in the year 2016 and analyzed the space-time dynamics of the water quality of the river, the increase in pollution in the period 2011–2016, and the water quality of the Atoyac River used for agricultural irrigation and human consumption in the population of Emilio Portes Gil, Ocoyucan, based on official Mexican standards (NOMs). The anoxic state of the river was demonstrated (~1.47 mgO₂/L) and the high organic pollution, particularly in drought, as well as the presence of large populations of coliform bacteria, and 11 enterobacteries of pathogenic importance. The pollution recorded an average increase of 49% in the period 2011-2016, and the values of Fe, Al, Pb, and Cd in variable percentages. It was evidenced that water for irrigation and wells is contaminated with fecal bacteria (104–549 NMP/100 mL), including pathogenic. In wells, the concentration of heavy metals was 5 times higher in drought. These results represent a serious threat for the population of Emilio Portes Gil and the environment in the metropolitan area of Puebla.

This paper aims to investigate carbon monoxide (CO) concentrations on roadways of Karachi, potential blood levels carboxy-hemoglobin (COHb) in Karachi. Geographical information system (GIS) was used for spatial analysis of diseases potentiality while an interpolation technique has been applied for surface generation with town boundaries and later evaluates risk areas.The higher concentration of carbon monoxide in the ambient is mainly due to automobile emissions. The City center and CBD areas are more perilous.

Epiphytic lichens are well-known indicators of air contamination. The chemical composition of lichens is affected by the concentration of pollutants in the environment. Usually, researchers assess long-term variations in trace elements or other pollutants in the study area or identify the spatial features of air contamination. The aim of this study is to create a database of trace element concentrations in the samples of the epiphytic lichen Hypogymnia physodes growing in the Kaliningrad region. The database can be used as a ‘reference point’ for monitoring studies. Another objective is to identify the spatial patterns of iron, manganese, nickel, cadmium, silver, lead, strontium, rubidium, and calcium in the Kaliningrad region. The samples of wild lichens were collected from pine and birch trees 1.2-1.8 m from the bases of the threes, using a regular grid, in August 2010. One-two-year-old thalli were used in the chemical analysis. The metals Ag, Cd, Cu, Pb, Ni, Fe, Mn, and Zn were determined by AAS (Mn, Fe by flame AAS and the others by ETA-AAS) and the elements Sr, Rb, and Ca by X-ray fluorescence. The concentration of metals in the western coastal area (the Sambian or Kaliningrad Peninsula) is higher than it is in the central and eastern parts of the region. Principal component factor analysis was carried out to detect and characterise different pollution sources and to identify the most polluted areas. The factors of metal emission were described. The authors examined the features of the spatial distribution of trace elements. Prevailing winds are form south-west. Therefore, the highest concentrations of trace elements were found on the Sambian peninsula and on the coasts of the Vistula and Curonian Lagoons. The high concentrations of trace elements in the samples of the lichen H.physodes, which were observed in the coastal part of the region, are associated with human impact and subsequent pollution. The chemical composition of lichens on the Sambian peninsula may have developed under the impact of both local pollution sources – vehicles, thermal energy facilities, and ports – and such factors as transboundary traffic and sea spray.

Climate change poses a significant risk to the environment and public health, leading to extreme weather patterns, rising sea levels, and loss of biodiversity. The relationship between air pollution from African dust and climate change demonstrates its critical role in trapping heat in the atmosphere, resulting in heat-related illnesses, heart problems, and respiratory issues. This Research points to the detrimental effects of pollutants such as smog, dust, acid rain, and ozone depletion on ecosystems, highlighting the importance of using Geographically Weighted Regression modeling and MODIS-NDVI analysis to address air pollution. Particulate Matter (PM 2.5-10) and ozone levels can have negative impacts on respiratory and cardiovascular health. Proactive steps, such as implementing clean energy technologies and enforcing stricter pollution regulations, are necessary to protect public health. Acting is crucial to addressing these global challenges and creating a cleaner, healthier future for future generations, underscoring the need for climate justice commitment.

The detection of complex formations, initially suspected to be oil spills, is investigated using atmospherically corrected multi-spectral satellite images and deep learning techniques. Several formations have been detected in an inland lake in Northern Greece. Four atmospheric corrections (ACOLITE, iCOR, Polymer, and C2RCC) that are specifically designed for water applications are examined and implemented on Sentinel-2 multispectral satellite images to eliminate the influence of the atmosphere. Out of the four algorithms, iCOR and ACOLITE are able to depict the formations sufficiently; however, the latter is chosen for further processing due to fewer uncertainties in the depiction of these formations as anomalies across the multi-spectral range. Furthermore, a number of formations are annotated at a pixel level for the 10 m bands (Red, Green, Blue, and NIR), and a deep neural network (DNN) is trained and validated. Our results show that the 4-band configuration provides the best model for the detection of these complex formations. Despite not being necessarily related to oil spills, studying these formations is crucial for environmental monitoring, pollution detection, and the advancement of remote sensing techniques.

Generating electricity from coal combustion is highly associated with ongoing pollution problems that negatively impact the environment. Coal fly ash (CFA) is a predominant waste by-product of coal combustion which is disposed of in exposed ash dams constructed in the vicinity of power stations. Its disposal requires a large piece of land and therefore more land is converted to unproductive disposal sites, degrading the ecosystem. This waste material is classified as a hazardous substance in South Africa due to unacceptable levels of inorganic and persistent organic pollutants and its potential for dust creation. CFA is recycled and sold to the building and construction sectors, but the rate of its utilization is far less than the production rate resulting to high volumes that is stockpiled in disposal sites. More than 500 million tons CFA is produced yearly and over 200 million tons yearly remain unused globally and more CFA will continue to be produced due to high consumer energy demands, especially in countries with heavy reliance on coal for power generation. In this context, the paper discusses production of CFA, pollution problems due to its disposal, examines existing gaps within the scope of ash dam restoration processes and presents opportunities offered by phytoremediation (a low-cost and environmentally friendly technology that utilizes plants to restore the degraded environments). Ecological restoration through the use of socio-economically valuable plants (aromatic plants, legumes and grasses) has potential in addressing societal challenges and consequently impacting positively the livelihood of communities.

The Lobo reservoir designed to supply water to the Daloa city populations (Central west of Côte d'Ivoire) is facing the phenomenon of eutrophication due to the agricultural plots located upstream the reservoir inputs. Studies have highlighted the reservoir pollution and sedimentation problem. This study was initiated to provide a simple and effective solution to the eutrophication problem. The main objective is to determine the potential optimal dimensions of a grassed strip in order to limit the eutrophication phenomenon of the Lobo reservoir. The sizing of this grassed strip was done using the VFSMOD model. The flow from the pollution source plots was simulated and integrated into the model. The different scenarios tested from the band width variation have concerned the return periods of 1 and 2 years. The results obtained revealed that for the one-year return period, the grassed strip to be installed should have a width of 12.70 m in order to reduce by 70% the flow entering the strip considering the diffuse runoff over a length of 300 m. For the two-year return period, a width of 22.95 m should be required with the same length. The scenarios showed that a grassy strip width equal to 3 m should allow a reduction of 75% of upstream sediments.

The Tisza River is the longest tributary of the Danube, draining the eastern part of the Carpathian Basin (Central Europe). Five countries share its catchment with different waste production and management practices. Large amounts of waste, including macroplastics (MaPs), are washed into the river. Some of the litter is trapped by the riparian vegetation forming litter accumulations. The study aimed to map the amount of litter by a citizen science program and remote sensing data and to compare the MaP data to the amount of microplastic fragments in sediments. Volunteers reported 3216 riverine litter accumulations from five countries along the entire length of the Tisza (2016–2022). The results suggest that low flow conditions (e.g., impoundment by dams) support litter and MaP trapping. The volume of large accumulations registered by the citizens showed a good correlation with the area of drifting litter revealed on Sentinel-2 images (2015–2021) using machine learning algorithms. Though the MaPs probably fragmentate during their fluvial transport, no clear connection was found between the volume of litter accumulations and the mean microplastic fragment content of sediments (2019–2022). The “Clean Tisza Map“ reveals the high degree of stranded pollutants along rivers and supports public cleanup activities.

This review paper presents a comprehensive synthesis of current knowledge on the contamination of water systems by polycyclic aromatic hydrocarbons (PAHs). PAHs, organic contaminants characterized by two or more fused aromatic rings, are notably problematic due to their persistence, bioaccumulation, and significant health risks. The review commences with an examination of various sources of PAHs in aquatic environments, encompassing both anthropogenic activities, such as industrial discharges, urban runoff, and oil spills, and natural phenomena including volcanic eruptions and wildfires. Subsequently, the discussion shifts to the distribution patterns of PAHs within different aquatic ecosystems, with an analysis of factors that influence their transport. Considerable focus is placed on the entry mechanisms of PAHs into water systems and their interactions with diverse environmental matrices. Additionally, the ecotoxicological effects of PAHs on aquatic life are scrutinized, with particular emphasis on molecular, individual, and ecosystemic impacts. This includes an exploration of PAH bioaccumulation in aquatic organisms and their potential mutagenic and carcinogenic consequences. The review further addresses the challenges associated with detecting and quantifying PAHs in aquatic settings, reflecting on the advancements in analytical methodologies and the complexities introduced by their varied physicochemical properties. The paper concludes with a summary of existing regulatory frameworks and guidelines governing PAH contamination in water systems, underscoring the imperative for global collaboration in the monitoring and management of PAH pollution.

BACKGROUND AND OBJECTIVE: The use of biomass for cooking carries significant health implications and can lead to adverse environmental issues such as deforestation, greenhouse gas emissions, and erosion. Despite these concerns, there is a lack of information about the nature and extent of cooking emissions in many developing countries. To address this gap, a study was conducted to assess cooking emission levels and their associated health effects among households in Dodoma City, Tanzania. METHODS: A descriptive cross-sectional design was conducted, involving 285 households in the peri-urban area of Dodoma City, Tanzania. A combination of questionnaires, observational checklists, and sampling devices (Aeroqual series 500 for Carbon Monoxide and Temptop PMD 351 for Particulate Matters) were employed for data collection, adhering to established protocols. Additionally, lung function tests were conducted with consent from the primary household cooks. Collected data were entered into an Excel spreadsheet and analyzed using STATA 17 software. FINDINGS: Out of 285 participants, 74.7% predominantly use charcoal for cooking, with 68.4% having outdoor kitchen setups. Significant differences in pollutant concentrations were observed across various fuel types (P=0.0001), with firewood emitting higher levels of particulate matter and carbon monoxide. Carbon monoxide concentrations during cooking were 6 times higher for firewood, 5 times higher for charcoal-gas, and 3 times higher for charcoal compared to WHO daily average limits. Additionally, a positive correlation between pollutant concentrations was noted (P-value = 0.0000). Lung problems 17.8% followed by eye irritation 15.7% were mentioned by those who claimed to know the health effects associated with cooking emissions. In addition, the spirometry test indicated that the majority of the participants had % predicted >80 while only 19% had % predicted below 50. CONCLUSION: Charcoal and firewood remain the primary cooking fuels in the study area despite their significant negative impacts. Our findings highlight a lack of awareness among community members regarding the health effects of biomass cooking emissions and insufficient guidance on constructing healthy kitchens. To address this, enforcing building standards, raising health awareness, and ensuring affordable access to modern fuels are crucial steps. These measures are essential for promoting healthier cooking practices and mitigating the adverse effects on households.

Thermaikos Gulf (TG) is a semi-enclosed, river-influenced, marine system situated in the eastern Mediterranean Sea, sustaining both urban coastal regions and ecologically preserved natural areas. Facing a plethora of environmental and anthropogenic pressures, the TG serves as a critical nexus where human activities intersect with marine ecosystems. The second largest city of Greece, Thessaloniki, is located in the northern part of the gulf, while a large environmentally protected zone with multiple river deltas is lying along its western coasts. The quality and health of the TG’s marine environment are tightly linked to the socioeconomic activities of the coastal communities comprising approximately 1.5 million inhabitants. The main features of TG’s environmental dynamics and ecological status have been scrutinized by dedicated research endeavours during the last 50 years. This review synthesizes the seminal findings of these investigations, offering an evaluation of their contribution to research, their present collective impact, and their trajectory toward the future. A severe deterioration of the TG’s environmental quality was detected in the 1970s and 1980s when treatment of urban wastewater was completely absent. A steady trend of recovery was observed after the 1990s, however without achieving, so far, the goal of a “good environmental state”, mandated by national legislation and European directives. The most important research gaps and uncertainties are also discussed and specific recommendations for the improvement of monitoring and understanding about the physical, biochemical, and ecological state of the gulf are provided. The most significant discrepancy is related to the fragmentary monitoring of the TG in both space (partial coverage) and time (temporal gaps), which has been intensified after 2010 due to the reduced funding for environmental research and protection under the severe Greek economic recession. This review aspires to highlight the importance of bolstering monitoring initiatives that can provide continuous observations and further understanding on the TG's ecological and physicochemical conditions. Targeted recommendations, aimed at ameliorating the fragmented monitoring processes, are also provided, advocating for a holistic approach that can safeguard the ecological integrity of the Thermaikos Gulf and uphold its role as a crucial link to marine biodiversity and sustainability in the Mediterranean basin.

Climate change, recognized as a global crisis, is not only altering our environment but also significantly impacting human health. Particularly, its influence on non-communicable diseases (NCDs), a leading cause of global mortality, is becoming increasingly evident yet underexplored. This review aims to synthesize current research on the impact of climate change on NCDs, addressing a critical gap in our understanding of how environmental changes affect human health. We examine the complex interplay between climate change and NCDs, drawing insights from recent studies that highlight the adverse effects of climate variables on chronic diseases, such as cardiovascular and kidney diseases, and the role of food and nutrition security in this nexus. Furthermore, the review explores the disproportionate impact on vulnerable regions and populations, particularly in Pacific Island countries and territories, underscoring the urgent need for context-specific solutions and a cross-sectoral approach. By integrating findings from various disciplines, this review aims to inform policy and public health interventions, highlighting the necessity of collaborative efforts to mitigate the burgeoning burden of NCDs in a rapidly changing climate.

The bioindicator potential of seagrass ecosystems in coastal trace metal monitoring is low for tropical island ecosystems. This study evaluated the bioindicator potential of six seagrass species exposed to anthropogenic trace metal pollution in the Andaman and Nicobar Islands (ANI) of India. Sediment and seagrass biomass, samples were analyzed for trace metals (Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn) from four locations of ANI exposed to anthropogenic contamination. Geo accumulation Index values indicated moderate trace metal contamination in seagrass sediment. Seagrass trace metal accumulation from sediment was both species-specific and location- specific for ANI. Small seagrass species such as H. ovalis, H. beccarii and H. uninervis accumulated the maximum concentration of six trace metals (Cr, Cu, Fe, Ni, Pb, Zn) in their tissues compared to big seagrass species like T. hemprichii and E. acoroides of ANI. This study indicates leaves of small seagrass and roots of big seagrass species can serve as short- and long-term bioindicators respectively, of coastal trace metal contamination in tropical islands of ANI.

Background: Parkinson's disease (PD) is a global disease. However, there is a lack of research specifically focused on the AfrAbia population. Climate change, driven mainly by global warming, is linked to detrimental health impacts, including an increased frequency and intensity of heat waves. Neurological diseases, including neurodegenerative syndromes like Alzheimer's disease, Parkinson's disease, and motor neuron illnesses, have been increasingly seen and recorded in scientific literature. Although there is much literature demonstrating the growth in neurodegenerative disorders, the relationship between environmental variables such as global warming, air pollution, heavy metals, and pesticides and the higher occurrence of these illnesses is still unknown. Objective: The current article primarily aims to examine the relationship between climatic changes, air pollution, pesticides, heavy metals, and the occurrence of PD. Initially, we evaluate the influence of exposure to these variables on the cause or origin of Parkinson's disease. In addition, we will investigate how these variables disrupt processes such as excitotoxicity, oxidative stress, and neuroinflammation, all of which are strongly linked to Parkinson's disease (PD). Conclusions: This research presents a plausible rationale for the adverse effects of environmental influences on the brain, which are pivotal in the progression or onset of Parkinson's disease from an AfrAbian standpoint.

Urban gardens have important social, environmental and economic roles in big cities, contributing to their sustainability. However, food production in urban gardens may be compromised due to soil pollution that resulted from decades of industrial non-regulated environmental activity and mobile transport. In this study, 12 soils from the urban agricultural area of Rome (Italy) were analyzed for the metals Be, Ba, Pb, Co, Ni, V, Zn, Hg, Cd, As, Cu, and Cr. All but one of the soils under analysis were characterized by at least one metal concentration above the threshold limit defined by the Italian Legislative Decree 152/2006 (ILD) for agricultural soils. Multivariate analysis showed that the soils could be classified into five clusters: clusters I and II had relatively lower mean metal concentrations; clusters III, IV, and V had relatively higher mean metal concentrations with several metal concentrations above the threshold proposed by ILD. Three factors contributing to the variability of the metal’s concentration in the soils under investigation were identified: geological factor, related with metals As, Ba, Be, and V; anthropogenic factor, related with Pb and Cu; and, a mixed factor related with Co, Cr, Ni, and Zn. High metal content may limit the utilization of urban soils as urban gardens for food production.

Today, air pollution is the greatest threat to organismal healthspan. The environment of our planet earth, the habitat of over eight billion humans and estimated twenty billion billions other animals, is contaminated with a wide variety of pollutants. Unfortunately, humans, out of billions and billions of living organisms on earth, are solely responsible for polluting the environment through emitting pollutants like particulate matter from industry, fuel engine vehicles, biomass combustion, toxic fumes from blasting, and wildfire. In the modern world, human-caused air pollutants induce massive oxidative stress and inflammation, the major contributors in initiation and progression of many diseases including pulmonary, cardiovascular, renal, hepatic, reproductive, neurological, mental, and accelerated biological aging. The provocative question is the following: how can we solve this human-created problem? As it is not realistic to clean the environment at once from human-caused pollution, initiatives have been undertaken to develop novel therapeutic approaches to control air-pollutant-induced oxidative stress and inflammation to protect humans from pollution-induced devastating diseases. In this article, I discuss the key findings of numerous recent preclinical studies documenting first, the role of air pollutant PM2.5 in augmentation of inflammation, oxidative stress, and associated diseases; and second, the efficacies of different natural and synthetic compounds in amelioration of PM2.5-induced oxidative stress, inflammation, pyroptosis, and associated pathologies.

Wildfires are a rising environmental threat which health impact remains poorly documented, in particular beyond the fire period. This ecological study investigates changes in health conditions before, during, and after two consecutive wildfires that occurred in France´s Gironde district in the summer 2022. Electronic records from the district´s emergency medical communication centre were used to identify calls with respiratory and cardiovascular diseases, and two specific subgroups of those, asthma (all ages and 0-5 years) and cardiac arrest, respectively. Compared to before the fires, respiratory disease cases were fewer during each fire (OR = 0.85, 95% CI: 0.79, 0.90 and OR = 0.62, 95% CI: 0.58, 0.67, respectively), cardiovascular disease cases, more common during the second fire, and asthma cases, higher following the fires (ORall ages= 1.85, 95% CI: 1.56, 2.21 and ORchildren= 3.52, 95% CI: 2.62, 4.80). Asthma cases also rose during the same calendar time in 2021, but to a lesser extent. In sum, except for asthma, emergency calls data in Gironde reveal few significant potentially smoke-related symptoms around fire periods, apart from post-fire asthma. Whether the effects are smoke- or season-related remains to be determined, preferably using additional data sources.

Acid in-situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. As some toxic and harmful substances might be produced by the chemical reactions among the injected sulphuric acid, the groundwater, and the porous media during leaching processes, the pollution control of the mining plan for ISL is important. In this study, a three-dimensional reactive transport modeling (3DRTM) was applied to decide the pollution control mining plan, considering the partial penetration through wellbore in confined aquifer and complex chemical reactions between main minerals. Based on the 3DRTM, different pumping ratio and non-uniform injection schemes were compared. The results show that the preferential pollution control mining plan is non-uniform injection ratio equal 0.1. By analyzing the characteristics of water table and streamline, it is concluded that the scheme has a strong hydraulic capture effect. In this scheme, the concentration of UO22+, H+, SO42- obtained by 3DRTM is lower. The inner well injection rate is 194.09 m3/d, the outer well injection rate is 158.89 m3/d, and the pumping rate is 264.00 m3/d. A reasonable suggestion is to adopt non-uniform injection mining mode in ISL.

Driven by industrialization and urbanization, urban air pollution can increase respiratory, heart, and cerebrovascular diseases, and thus mortality rates; as such, it is necessary to improve air quality through the consideration of individual pollutants and emissions sources. In South Korea, national and local governments have installed urban and roadside air quality monitoring systems. However, stations are lacking outside metropolitan regions, and roadside stations are sparsely distributed, limiting comparisons of pollutant concentrations with vehicle traffic and floating population levels. Local governments have begun using mobile laboratories (MLs) to supplement the fixed measurement network and investigate road pollution source characteristics based on their spatiotemporal distribution; however, the collected data cannot be used effectively if they are not visualized. Here, we propose a method to collect and visualize global information system (GIS)-based air quality data overlayed with environmental variables to support air quality management measures. Spatiotemporal analyses of ML-derived data from Bucheon, Korea, confirmed that particulate and gaseous pollutant concentrations were high during typical commuting hours, at intersections, and at a specially managed road. During commuting hours, the maximum PM10 concentration reached 200.7 µg/m³ in the Nae-dong, Gyeongin-ro, and Ojeong-dong ready-mix concrete complex areas, and the maximum PM_2.5 concentration was 161.7 µg/m³. The maximum NOx, NO₂, and NO levels of 1.34 ppm, 0.18 ppm, and 1.18 ppm, respectively, were also detected during commuting hours. These findings support the need for targeted management of air pollution in this region, and highlight the benefit of comprehensively comparing road levels, driving speed, and traffic levels when identifying hotspots of air pollution. Such analyses will contribute to the development of air quality management measures customized to regional characteristics.

Spectacularly, particulate matter pollution influences human health by aggravating numerous diseases and causing premature deaths. In order to eliminate its concentration in the ambient air, plant species can act as natural bio-filters and capture, degrade, and metabolize air pollutants inside their foliage. In a study carried out at three sites with different pollution levels and plant types. The immobilization efficiency of Particulate Matter (PM) was investigated in the leaves of three species (shrub, climber, and herb) in the southwestern of Japan with a time gap of 14 days. Two healthy mature leaf samples of each specimen were carefully collected and analyzed using the gravimetric analytical method. A significant quantity of PM in three-size fractions with aerodynamic diameters ranging between (0.1-100 μm) was captured inside the leaf foliage of the analyzed species. Fine particles (2.5 -10 μm) dominated the highest portion of the PM deposition captured by the analyzed species with 70.6 μg.cm-2(39.5%). Shrub species represented with Elaeagnus pungens proved to be the most efficient species among the analyzed species. Leaf traits such as grooves, trichomes, roughness, and margin are considered key factors associated with positive PM deposition, whereas the total surface area of the leaves had no direct correlation to PM deposition.

An important indicator of human-related pollution in watersheds is dissolved oxygen (DO). The DO is highly dependent on both space and time characteristics of the watershed and is directly linked to eutrophication, which impairs the development of both the aquatic fauna and flora, also negatively impacting the water quality. Aspiring to reach a more accurate and precise forecasting approach to predict levels of DO, the present work proposes new graph-based and transformer-based deep learning models. The models were trained and validated for the Credit River Watershed, and the results were compared with both benchmarking and literature-found approaches. The proposed Graph Neural Network Sample and Aggregate (GNN-SAGE) model was the best-performing approach, reaching coefficient of determination (R2) and Root Mean Squared Error (RMSE) values of 97% and 0.34 ppm, respectively. The findings from the Shapley additive explanations (SHAP) indicated that the GNN-SAGE benefited from spatiotemporal information from the surrounding stations, improving the model’s results, and that temperature is a major input attribute for determining future DO levels. The results established that the proposed GNN-SAGE model stands as a state-of-the-art solution for DO forecasting, with potential for real-time water quality applications.

This publication aims to disseminate a step-by-step process that walks through the conceptualization and building of a low-cost (~ $150 monitoring device for airborne fine particulate matter (PM2.5), based on miniaturized sensors and components. Details on the implementation of the hardware and software are provided which facilitate the data acquisition, capture and analysis. The central components and their setup discussed in what follows include: the sensor device (called “P.ALP” – Ph.D. Air quality Low-cost Project), Arduino IDE (Integrated Development Environment) and R code (open-access software). A monitoring device for PM2.5, using low-cost sensors and technologies was successfully conceptualized, designed, and implemented. The P.ALP monitoring system was designed and developed to be a basic device, which can be further customized and implemented using the wide range of low-cost sensors available on the market.

ST-segment elevation myocardial infarction (STEMI), a major cause of mortality worldwide, has been shown through epidemiological studies to have a relationship with short-term exposure to air pollutants; however, the association between air pollutants and the outcome of STEMI has not been well studied. The aim of this study was to estimate the impact of air pollutants on the outcomes of STEMI. Data on particulate matter <2.5 μm (PM2.5), <10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) at each of the 11 air monitoring stations in Kaohsiung City were collected between January 1, 2012, and December 31, 2017. Medical records of non-trauma patients aged > 20 years who had visited the ED with a principal diagnosis of STEMI were extracted. The primary outcome measure was in-hospital mortality. After adjusting for potential confounders and meteorological variables, we found that an increase in the interquartile range (IQR) in NO2 was associated with an elevated risk of in-hospital mortality in patients with STEMI. Moreover, during the warm season, an IQR increase in NO2 corresponded to a higher risk of in-hospital mortality in patients with STEMI on lag 3 (OR=3.266; 95% CI:1.203–8.864, p=0.02). Conversely, an IQR increase in PM10 was associated with an increased risk of in-hospital mortality in patients with STEMI on lag 3 (OR=2.792; 95%CI:1.115–6.993, p=0.028) during the cold season. Our study suggests that exposure to NO2 (during warm season) and PM10 (during cold season) may contribute to a higher risk of poor prognosis in patients with STEMI.

The article analyzes two existing social, technical and economic problems which the world community shall focus on and pay special attention to.

This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections and for the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that together with the adoption of COPERT based emission factors allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants in comparison to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, stressing the positive contribution of EVs and new, "greener" vehicles, and setting new challenges for the further improvement of the sector beyond the 2030 outlook.

During the COVID-19 lockdown in Wuhan, transportation, industrial production and other human activities declined significantly, as did the NO2 concentration. In order to assess the relative contributions of different factors to reductions of air pollutants, sensitivity experiments were implemented by random forest (RF) model, with the comparison of contributions of meteorology, road traffic, and emission sources between different periods. Besides, an emulator was operated to suggest an appropriate limit for control of transportation. The RF models showed different mechanisms for air pollutants. Within-city Migration index (WMI) was more important in the normal, pre-lockdown and post-pandemic model while Out-Migration Index (OMI) was emphasized in the lockdown model. In the COVID-19 lockdown period, 73.3% of the reduction can be attributed to the decreased road traffic, showing massive impact of road traffic on the air quality. In the post-pandemic period, meteorology controlled about 42.2% of the decrease and emissions from industry and household controlled 40.0% while road traffic only contributed to 17.8%. It was suggested that priority of restriction should be given to road traffic within the city. A limit of less than 40% on the control of the road traffic can get a better effect, especially for cities with severe traffic pollution.

This paper describes the use of a new obtrusive light module of the Illumina v2 model to estimate the light that may enter bedroom windows. We used as input to the model, 1- the sources’ flux and spectrum derived from the color images taken by astronauts from the international space station, 2- an association between source spectrum and angular emission, and 3- a per zone inventory of obstacles properties and lamp height. The model calculate the spectral irradiance incident to buildings’ windows taking into account for the orientation of the street. By using the color information from an ISS image, we can classify pixels as a function of their spectra. With the same image, it is also possible to determine the upward photopic radiance for each pixel. Both serve as inputs to the model to calculate the spectral irradiance on any window. By having the spectral irradiance, it is possible to determine the Melatonin Suppression Index and the photopic irradiance on the window. Such information can later be used to perform epidemiological studies. The new methodology is applied to the case of Montréal in Canada for a set of houses’ locations. The computations are made for 2013 (pre-LED era).

This article analyses the environmental impact of the measures imposed during the SARS-CoV-2 pandemic. We compare the evolution of atmospheric pollution levels in recent years and during lockdown, and assess the effects of the decrease in mobility and changes in patterns and lifestyles during the latter period. Thus, the reduction in the risk to human health brought about by the improvement of air quality during the months of confinement through the use of dose-response functions is estimated. The focus of the case study is the island of Tenerife. The island of Tenerife has been selected because it can serve as an example for other sites in Europe. We distinguish between the three areas with the highest population concentrations: the Metropolitan, Southern, and Northern areas. The impacts of air pollution and its relationship with changes in consumption and activity patterns are clearly distinguishable. Therefore, the lessons learned can be easily extrapolated to other areas, in both island and mainland contexts.

Experiences of homelessness, although widely varied, are characterized by extensive time in public spaces, often outdoors. However, there has been little empirical research about the ways in which environmental factors affect individuals experiencing homelessness (IEHs). Therefore, the purpose of this study was to use an environmental justice approach to understand how cardiopulmonary health of IEHs is affected by episodic poor air quality in Salt Lake County. It was hypothesized that people who had experienced unsheltered homelessness and those who had been experiencing homelessness for longer periods of time would report greater health difficulties from poor air quality exposure. Through a combination of in-person semi-structured interviews with IEHs (n = 138) and access to corresponding state-based service provider databases, researchers examined both overall descriptives of and relationships between types (sheltered and unsheltered) and duration (chronic and non-chronic) of homelessness. More than 61% of IEHs reported physical reactions to air pollution, 37% reported air pollution-related emotional stress, and more than 89% had sought medical attention for a condition related to air pollution. Findings indicate that while IEHs report a number of health effects related to poor air quality, there were no significant differences between individuals based on either sheltered status or duration of their experiences of homelessness. This study provides an initial empirical inquiry to understand how environmental disamenities negatively influence IEHs, as well as noting that sheltered status and duration of homelessness are less impactful than originally hypothesized.

High levels of air pollution can contribute to high rate of the COVID-19 outbreaks. Air pollutants induce oxidative stress, inflammatory process, immune imbalance and coagulation at systemic level, making the organism susceptible to complications caused by various pathogens, including viruses, resulting in a possible important damage co-factor. Sperm cells are highly sensitive to the pro-oxidant effects of environmental pollutants, and may represent an important alarm bell indicating that the burden of environmental pressure in a certain area is causing damage to humans. A comparison of the maps of COVID-19 case fatality rates, male infertility rates and air pollution may suggest a way to understand the dynamics of the virus impact. Semen quality may be considered as an early and sensitive environmental marker, and also a potential susceptibility indicator to viral insults (including SARS-CoV-2 ) in heavily polluted areas. Therefore, assessing the burden of environmental exposure of a given population and its potential susceptibility to insults through early biological stress indicators may be helpful for predicting the risk of the adverse effects by the SARS-CoV-2 epidemic .

A recent study found that a 3ppb increase in O₃ ambient concentration was associated with an increased progression of 0.18 percentage points in percent emphysema and that such increase was equal to smoking 20 cigarettes per day for 29 years. A simple estimation of population attributable fraction shows that COPD diagnoses due to smoking are actually 30 times more than those attributed to a 3 ppb increment in O₃ concentration. Labelling ozone pollution as the new smoking may distort perception of the risks and hinder proper response to real life threatening risk such as smoking.

Inflammatory allergic and nonallergic respiratory pathologies often co-exist. The root cause is not clear. This paper demonstrates that it is ascribable to protons (H⁺) released into cells by exogenous and endogenous acids. The hypothesis of acids as the common cause stems from two considerations: a) it has long been known that exogenous acids present in air pollutants can induce the irritation of epithelial surfaces, particularly the airways, inflammation and bronchospasm; b) according to recent articles, endogenous acids, generated in cells by phospholipases, play a key role in the biochemical mechanisms of initiation and progression of allergic responses. Therefore, the intracellular acidification and consequent Ca²⁺ increase, induced by protons generated by either acid pollutants or endogenous phospholipases, may be the causal mechanism of the multimorbidity of these diseases, and environmental acidity may contribute to their spread.

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

The crucial stages in the geochemical evolution of the Earth’s crust, ocean, and atmosphere could be explained by the assumed low-energy nuclear reactions (LENR) that are triggered by seismic activity. LENR result in the fission of medium-weight elements accompanied by neutron emissions, involving Fe and Ni as starting elements, and C, N, O as resultants. Geochemical data and experimental evidences support the LENR hypothesis. A spectral analysis of the period 1955-2013 shows common cycles between interannual changes in atmospheric CO2 growth rate and global seismic-moment release, whereas the trending behavior of the atmospheric CO2 was in response to the anthropogenic emissions. Assuming a correlation between such seismic and atmospheric fluctuations, the latter could be explained by cycles of worldwide seismicity, which would trigger massively LENR in the Earth’s Crust. In this framework, LENR from active faults could be considered as a relevant cause of carbon formation and degassing of freshly-formed CO2 during seismic activity. However, further studies are necessary to validate the present hypothesis which, at the present time, mainly aims to stimulate debate on the models which regulates atmospheric CO2.

As the necessity for safety and aesthetic of nightscape have arisen, the importance of nightscapes (i.e., nighttime landscape) planning has garnered the attention of mainstream consciousness. Therefore, this study is to suggest the guideline for nightscape planning using electroencephalography (EEG) technology and survey for recognizing the characteristics of a nightscape. Furthermore, we verified the EEG method as a tool for landscape evaluation. This study analyzed the change of relative alpha power and relative beta power and self-reporting of participants in order to investigate the correlation between EEG and fear according to twelve nightscape settings. Our findings indicated the corresponding measures of fear vary accordance with whether there was people or not, and the environmental settings (Built Nightscape Images; BNI vs Natural Nightscape Images; NNI). Based on our physiological EEG experiment, we provided a new analytic view of the nightscape. The approach we utilized enables a deeper understanding of emotional perception and fear among human subjects by identifying the physical environment which impacts how they experience nightscapes.

High mountain areas are an appropriate indicator of anthropogenic lead (Pb), which can reach the remote mountain ranges through long distance atmospheric transport. We compared the content of Pb in ecologically equivalent rodent species from Tian-Shan with European mountain ranges Tatra, Vitosha and Rila mountains. We used bone tissues from terminal tail vertebrae of small rodents for detection of Pb levels by using electrothermal atomic absorption spectroscopy (AAS). The tail bones of Tian-Shan rodents had significantly lower Pb levels than snow voles from Tatra mountains, but there was no significant difference in comparison with Vitosha and Rila mountains. We can conclude that Tian-Shan shows lower pollution by Pb than Tatra mountains, what may be a reason of longer lasting industrialization of north-western Europe and strongly prevailing west winds in Tatra mountains.

In China, environmental pollution generated via industrialization as well as the profound changes in the social structure and gradual maturation of the social hierarchy have jointly contributed to the Chinese people's increased environmental consciousness and appeals for environmental justice (EJ). Because of the absence of an EJ theory and a lack of empirical research focused on China, this paper proposes a ‘Pyramid Model’ for China’s EJ research that involves the following three factors: basic demographic and socioeconomic factors, U.S.-based EJ principles, and Chinese characteristics. A nationwide pilot analysis of environmental inequity at the prefecture level is conducted by empirically studying the association of demographics and socioeconomic status with sources of industrial pollution in China. The prefecture-based results are shown to be robust and indicate that areas inhabited by ethnic minorities and western regions in China carry disproportionate environmental burdens. However, a different picture for migrants is presented, revealing that Chinese migrants are not currently exposed to greater levels of industrial pollution, and relevant interpretations of these findings are provided. The results also show that environmental inequality associated with income level, which is observed in the U.S., does not occur in China.

Water pollution associated with flooding is one of the major problems in cities in the global South. However, studies of water quality dynamics during flood events are not often reported in literature, probably due to difficult conditions for sampling during flood events. Water quality parameters in open water (canals, rivers, and lakes), floodwater on roads and water in sewers have been monitored during the extreme fluvial flood event on 7 October 2013 in Can Tho city, Vietnam. This is the pioneering study of urban flood water pollution in real time in Vietnam. The results showed that water quality is very dynamic during flooding, especially at the beginning of the event. In addition, it was observed that the pathogen and contaminant levels in the floodwater are almost as high as in sewers. The findings show that population exposed to flood water runs a health risk that is nearly equal to that of being in contact with sewer water. Therefore the people of Can Tho not only face physical risk due to flooding, but also exposed to health risk.

The growing concern over heavy metal contamination in environmental and industrial settings has intensified the need for sensitive, selective, and cost-effective detection technologies. Electrochemical sensors, due to their high sensitivity, rapid response, and portability, have emerged as promising tools for detecting heavy metals. Recent years have seen significant progress in utilizing biopolymer-based materials to enhance the performance of these sensors. Biopolymers, derived from renewable raw materials, have garnered considerable interest in both science and industry. These biopolymer-based composites are increasingly recognized as superior alternatives to conventional non-biodegradable materials because of their ability to degrade through environmental exposure. This review provides a comprehensive overview of recent advancements in biopolymer-based electrochemical sensors for heavy metal detection. It discusses various types of biopolymers and bio-sourced polymers, their extraction methods, and chemical properties. Additionally, it highlights the state-of-the-art in applying biopolymers to electrochemical sensor development for heavy metal detection, synthesizing recent advances and offering insights into design principles, fabrication strategies, and analytical performance. The review underscores the potential of biopolymer-based sensors as cost-effective, eco-friendly, and efficient tools for addressing the pressing issue of heavy metal contamination in water and discusses their advantages and limitation. It also outlines future research directions to further enhance the performance and applicability of these sensors.

Chattogram is the port city as the busiest port of Bangladesh is there. Geographically, it lies besides the Bay-of-Bengal and Karnaphuly river. The city is currently stuck with urban flood and water pollution. Drainage congestion results in irregular flow of water which then ended in urban flood. Urban flood carries huge number of pollutants from the drains to the other water bodies. This study aims to investigate drainage congestion as the causal factor of urban flood and urban flood is the cause of water pollution. This study also aims to assess the impacts of water pollution in the study area. The findings highlight that drainage congestion causes irregular water discharge and overflow of water. A short time to rain results as the urban flood in the study area. The water of drainage system gets mixed with the urban flood which then carried into the karnaphuly river, lakes, khals, canals, ponds etc. The pollutants from the drain cause the water pollution. Study found that the drainage water is much more polluted in comparison to normal water quality parameters. The amount of pollutant is much more because of drainage congestion as the congested water gather much pollutants than the natural flow of water. Statistical analysis also found the significant correlation between drainage congestion and water pollution. However, the residents of the study area are the much more sufferers of the water pollution. They fall a victim to Cholera, Typhoid, hepatitis B, Dysentery, Dengue, Chikonguniya etc. water related diseases. Impacts on urban neighborhood as impacts on aesthetic beauty, impacts on drinking water, impacts on human habitat, impacts on environment, infrastructural impact, spread out of diseases among the residents etc. were found in this study. Impacts on urban environment as impacts on soil, impacts on atmosphere, impacts on human habitat, impacts on human health, impacts on road and other infrastructures etc. were investigated as well. This research also came up with the possible solution to mitigate the impacts of urban flood and water pollution in the study area.

One of the most pressing environmental problems contemporary civilizations confront is the ever-increasing amount of plastic waste. Because of their impact on every living thing, these wastes are seen as a major issue on a global scale. To counteract the harmful environmental effects caused by conventional disposal methods, it is critical to show that eco-friendly alternatives are viable. Biodegradation is one of the best eco-friendly methods for removing plastic waste. In this study, we aimed to identify bacteria from sewage wastewater treatment plants (SWW) that could degrade polyethylene. The bacterial strains isolated from sewerage wastewater were incubated for 120 days in 50 ml of minimal salt media (MSM) containing 60mg polyethylene. After four months, our research revealed that Bacillus tropicus (SH4) demonstrated significant potential, degrading poly-ethylene up to 21.6%. We observed the changes after biodegradation using FTIR, GC-MS, and SEM analysis. In conclusion, microorganisms extracted from sewage wastewater possess the ability to mitigate plastic contamination in aquatic ecosystems. Future proteomics and genome investiga-tions are necessary to elucidate the enzymes and metabolic processes implicated in plastic breakdown.

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 Clean Air Program currently implemented mainly involves the reduction, and ultimately the total elimination, of coal combustion in all heat sources of the municipal sector, which is identified in numerous publications as the main source of air quality degradation in cities. The program's goal, which timeframe covers the years 2018-2029, is a definite reduction in particulate pollution. The second part of the remedial activities, covering the years 2024-2034, mainly concerns the reduction of nitrogen oxide pollution, the main source of which is urban road traffic. In the latter case, the expected effects of introducing Low-Emission Zone (launched July 2024) in the city center are considered. According to the project, the zone's implementation will consist of five two-year stages, in which the car emission limits will gradually tighten. The paper compares the effectiveness of two being considered versions, differing in size zones.

The mechanism by which the human nose perceives an odor is complex and involves various chemical reactions in the transformation of the odorous molecule into an electrical impulse sent to the brain that returns the sensation of smell. The smell is classified and quantified, and its instrumental detection can be carried out through the “electronic nose”, an interactive device that lends itself to various applications. In the agri-food sector, the development of portable devices makes possible to smell foods and measure their level of deterioration and maturation; this is undoubtedly useful for reducing waste, identifying the best moment for food consumption, and improving the level of food safety. With regard to the environmental compatibility of materials and techniques for packing and laying conglomerates (for example bituminous), the problem of olfactory nuisance for the population residing in the neighborhood is still an unresolved problem. The approach based on electronic noses is very effective. The electronic nose also represents an important resource in the screening of respiratory pathologies, where there is the need to identify a rapid and reliable diagnostic test for pathologies such as pneumonia or seasonal flu. Environmental monitoring of pollutants is of particular relevance today and the electronic nose is an important candidate for the use in this field. The gas sensor market leverages physics, chemistry and materials engineering to develop highly sensitive, reliable and stable sensor platforms, capable of detecting very small amounts of gas molecules in the environment. To develop competitive gas sensing platforms, new materials are being considered, including polymers, nanostructured metal oxides and nanostructured carbon-based materials (CNTs). In addition to the experimental aspects, in particular Raman and electron spectroscopy techniques together with atomic force microscopy, theoretical-mathematical modeling plays an extremely important role in this sector, with particular attention to the case of micro and nanometric dimensions. Many efforts are now aimed in improving the sensitivity of these devices and this is related to the diffusion of carriers in them. The paper also offers an overview of the mathematical models relating to mechanical processes and dynamics at the micro-nanometric scale, lastly focusing on the Drude-Lorentz type models, with related more recent generalizations.

Recent studies releaved that the high production of reactive oxidative species due to exposure of fine or ultrafine particles are implicated in many chronical respiratory disorders. However, the poor standard of clinical data in sub-Saharan countries makes very difficult the assessment of knowledge of air pollution health impact in urban cities. Objective: the aim of this study was to evaluate distribution of respiratory disorders associated to exposure of air fine and ultrafine particles through changes of some oxidative stress biomarkers among motorbike drivers from two cities of Cameroon Methods: A cross-sectional survey using a standardized questionnaire was conducted in 2019 on 191 motorcycle drivers (MD) working in Douala and Dschang. Then, the activity of superoxide dismutase (SOD) and the level of malondialdehyde (MDA) were measured by colorimetric methods. The data of participants after clustered in Excel Microsoft were analysed and statistically compared using Spss 2.0 software. Results: The motorbike drivers recruited to both cities were aged from 21 to 40, with mean age of 29.93 (± 0.82). The distribution of respiratory disorders as running nose, cold, dry cough, chest discomfort, and breathlessness, was significantly increased among MD in Douala. According to results of biological assays, SOD and MDA, were significantly more increased among MD recruited in Douala, compared to those of Dschang. The change of these oxidative stress markers was significantly correlated with mobilization of neutrophils and Monocytes showing initiation and evolution of subjacent inflammatory reactions, and seemed to be significantly influenced by place of habitation of MD. Conclusion: Through this study it is confirmed the evidence of initiation and evolution of oxidative stress with long-term exposure to air fine or ultrafine particles among active people in Urban cities. Further studies should be conducted with more analysis to provide evidence cellular damage and dysfunction related to chronically exposure to fine air PM among active people in metropolitan of sub-Saharan Africa context.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

Heavy metal pollution poses a significant threat to global populations, particularly impacting human health. Developing countries, characterized by chemical engineering and mining industrial activities, often contribute to diverse heavy metal contaminants. Consumption of water contaminated with heavy metals, prevalent in such regions, can lead to severe health risks, including gastric cancer. Addressing the urgent issue of heavy metal pollution, this paper employs a bibliographic approach to explore the latest literature on heavy metal pollution. The study discusses recent research findings and potential methods for the treatment and mitigation of heavy metal pollution, emphasizing the pressing need for effective solutions to safeguard public health.

The amount and composition of litter was evaluated, during May and June 2021, at two urban beaches, i.e. La Victoria and La Cortadura, in Cadiz, SW Spain. Surveys were daily carried out in the morning and in the evening during the week−ends to quantify the daily accumulation of beach litter and relate it with the number of beach users, which was assessed at around 1:00 p.m. Litter amount was also related to clean-up operations that very mechanically and manually carried out each day very early in the morning. A total of 8108 items were collected at the two investigated sectors during the study period and beach visitors were quantified in each one of 22 surveys. Plastic was the most common material representing 82% in La Victoria and 68% in La Cortadura. The most common items were cigarette butts and small hard plastic fragments. Some hazardous litter items for beach visitors were identified such as broken glass. The number of visitors has been positively related to the amount of litter. Significant differences were seen in the litter abundance between the morning and afternoon assessments since the beaches are daily cleaned and show bins to facilitate litter disposal. Cleaning operations remove much of the litter items but always leave low quantities of small items uncollected. Efforts to prevent litter on these beaches should focus on informing visitors properly in order to avoid dumping and on improving clean-up operations.

Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules and emission ratios is required, in contrast to pristine locations, where reliance on a single or a few chemical tracers is frequently sufficient. We have characterized the prevalence of NMHCs fingerprints in the urban areas and quantified the correlation of windspeed with the concentration of these pollutants. eNose sensors and Air quality management stations provide the data to identify the emission sources of such pollutants. Based on our analysis, the average NMHC concentration in 2021 has been recorded 0.424 ppm at point 1 AQMS whereas at point 2 AQMS it was 0.256 ppm. Such outcomes could be attributed to the proximity of emissions sources, the direction and speed of the wind, or both. Moreover, traffic can be a major contributor to pollution levels in any urban area. More research based on a larger dataset is required before definitive conclusions can be drawn, and viable solutions can be proposed.

This study presents a comprehensive assessment of indoor particulate matter (PM) concentrations, focusing on PM1, PM2.5, and PM10 in five Primary Health Centers (PHCs): Arakale, Federal College of Agriculture (FECA), Iju, Oba-Ile, and Owode within Akure Local Government Areas in Nigeria. The primary novelty of this research lies in its detailed exploration of the toxicity potential of these PM fractions, providing valuable insights into the local air quality and associated health risks. The study assesses the health implications by calculating the toxicity potential (TP), Relative Risk (RR), Excess Risk (ER), and Attributable Fractions (AF) for cardiopulmonary and lung cancer mortality. The results reveal varying RR values for all-cause mortality, with Arakale showing a slight elevation (RR: 1.061), indicating potential health risks. ER values for cardiopulmonary mortality range from 14.728±7.25 to 19.04±0.38, emphasizing the substantial excess risk associated with long-term PM2.5 exposure. The study also uncovers AF for cardiopulmonary mortality ranging between 11.03±0.31 to 19.22±0.04, underscoring the significant contribution of PM to cardiovascular and respiratory health risks. Similarly, AF for lung cancer mortality ranges from 10.03±0.012 to 17.13±0.10, highlighting the substantial association between PM2.5 exposure and lung cancer risk. These findings underscore the urgent need for targeted air quality management strategies and public health interventions in the studied locations to mitigate the heightened health risks associated with particulate matter pollution. The calculated RR, ER, and AF values offer crucial insights into the complex relationship between PM exposure and adverse health outcomes, providing a foundation for informed decision-making and future research endeavors.

Rice cultivation is the main agricultural activity in Asia, and it results in an enormous amount of agricultural waste, that are usually disposed-off by burning, causing serious environmental health and climate problems. Pakistan is the tenth largest producer in the world and the fourth exporter of rice in the world. To date, there are no studies targeting Pakistan’s profile monitoring its contribution in open burning emissions from rice straw waste. This study presents the characterization of PCDD/Fs, PCBs and PAHs emissions from three samples of rice straw collected from the main rice cultivation regions of Pakistan (Punjab, Sindh and Azad Jammu and Kashmir) in relation to the role of metal-based agricultural additives. PCDD/Fs, PCBs and PAHs emissions were quantified using a fixed grid system biomass plant and measuring the macro-pollutants online and sampling the organic micro-pollutants and metals in isokinetic mode, followed by ISO and CEN standards methods. In addition, role of agrochemicals was monitored in terms of metal catalysis resulted in POPs emissions. This study provides the characterization of most relevant group of pollutants (metals, PCDD/Fs, PCBs and PAHs) as a result of agricultural waste combustion. The rice straw samples from AJK showed high values of organochlorine micro-pollutants compared to the values followed by samples from Punjab and Sindh, i.e., respectively, ∑PCDD/F (2594>1493>856 pg/Nm³) and ∑PCB (41>38>30 pg/Nm³). Whereas the organic micro-pollutants ∑PAH, indicators of incomplete combustion (PICs), were recorded high in the samples from Sindh followed by Punjab and AJK. This study supports the idea that the phenomena that lead to the formation of PCDD/F and PCB are influenced not only by poor combustion but also by the presence of metal catalysts or precursors in the burned fuel.

Quite a number of new metered parking systems have been introduced in recent years by the local authorities of various spa towns in Poland in connection with home zone conversion projects. The traffic signs posted in these locations were limited to the beginning and end of the demarcated parking area. Traffic circle (TC) is an example of traffic calming measures (TCM) used in home zones to slow down the traffic (case study – home zone in a small spa village). This article presents the results of a study investigating the speed reductions obtained with a home zone and traffic circle used as traffic calming measures. The indispensable speed surveys were carried out in relation to this study in two periods: in summer when the streets are crowded with tourists and in September with little pedestrian traffic. Two research hypotheses were formulated as part of the speed data analysis to verify the slowing effect of traffic circle and the relevance of traffic circles design parameters and location, road function and the surrounding streetscape. For each hypothesis statistical analyses were carried out using two nonparametric tests: two-sample Kolmogorov–Smirnov test and median test. The third research hypothesis formulated in this study was related to sustainable development factors related to fuel consumption and traffic-related air pollution including carbon dioxide, carbon monoxide, nitrogen oxide and hydrocarbons. This hypothesis was verified by estimating the amount of air pollution in the home zone under analysis in three different situations (scenarios): in summer with the travel speed reduced by pedestrian traffic to ca. 8–10 km/h and in September with a small number of pedestrians and 20–25 km/h resulting speed between traffic circles, reduced at traffic circle, and in a theoretical 30 km/h zone with 25–30 km/h assumed speed between traffic circles, dropping at traffic circle. These analyses confirmed the appropriateness of traffic circle as a home zone traffic calming measure, as long as its design is based on a detailed analysis of the relevant factors, including location, road function and the surrounding streetscape.

Traffic congestion is a persistent and challenging problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. Signalized intersections play a pivotal role in regulating traffic flow, and their efficiency has a direct impact on the overall traffic performance of a city. This study investigates the effect of traffic signal in managing traffic volume and reducing congestion and delays at signalized intersections through a comprehensive analysis of existing research, data collection, and simulations.The research begins by analyzing the traffic characteristics by an installed LiDAR sensor at E Cold Spring Ln – Hillen Rd intersection in Baltimore City, MD. When the signal at this intersection stopped working for some hours during a working day in September 2023, the LiDAR recorded vehicle and pedestrian counts, vehicle-vehicle and vehicle-pedestrian conflicts, and jaywalking events conflicts. The research aims to assess the impact of traffic signal failures on traffic flow, congestion, safety (V2V and V2P conflicts), and the frequency of jaywalking events before, during, and after improper performance of the traffic signal. Furthermore, this study explores the factors influencing traffic signal performance, including traffic demand, geometric layout, pedestrian interactions, and the integration of emerging technologies. The analysis results highlighted the importance of signal control systems existence at this intersection that can adjust signal timing in response to changing the real-time traffic conditions.Reduced congestion, minimized delays, and enhanced traffic flow are observed outcomes, contributing to a more sustainable and efficient urban transportation system. However, it is crucial to consider the trade-offs and challenges associated with traffic signal optimization, such as the potential for increased travel times for certain modes of transportation and the need for ongoing maintenance and updates. In conclusion, this study underscores the pivotal role of traffic signals in managing traffic volume and reducing congestion and delays at signalized intersections. Through evidence-based analysis and innovative signal control strategies, urban planners and transportation authorities can work towards creating more efficient, sustainable, and less congested transportation networks. The insights derived from this research can inform policy decisions and guide the development of future traffic management solutions, ultimately leading to improved quality of life in urban areas.