Search Results (41)

Organophosphorus pesticides (OPs), while pivotal for agricultural productivity, pose severe environmental and health risks due to their persistence and bioaccumulation. Existing detection methods, such as chromatography and spectroscopy, face limitations in field adaptability, cost, and operational complexity. To address these challenges, this study introduces a novel dual-mode photoelectrochemical–electrochemical (PEC-EC) sensor based on a Co,N-TiO₂@ZrO₂/3DGH nanocomposite. The sensor synergistically integrates zirconium oxide (ZrO₂) for selective OP capture via phosphate-Zr coordination, cobalt-nitrogen co-doped titanium dioxide (Co,N-TiO₂) for visible-light responsiveness, and a three-dimensional graphene hydrogel (3DGH) for enhanced conductivity. In the PEC mode under light irradiation, OP adsorption induces charge recombination, yielding a logarithmic photocurrent attenuation with a detection limit of 0.058 ng mL⁻¹. Subsequently, the EC mode via square wave voltammetry (SWV) self-validates the results, achieving a detection limit of 0.716 ng mL⁻¹. The dual-mode system demonstrates exceptional reproducibility, long-term stability, and selectivity against common interferents. Parallel measurements revealed <5% inter-mode discrepancy, validating the intrinsic self-checking capability. This portable platform bridges the gap between laboratory-grade accuracy and field-deployable simplicity, offering transformative potential for environmental monitoring and food safety management. Full article

The air quality in Mosul was adversely affected both directly and indirectly during and after the conflict phase, spanning from the occupation to the liberation of the city from ISIS (2014–2017). Direct impacts included the ignition of oil fields and sulphur deposits, as well as the use of military weapons and their propellants. Indirectly, the air quality was also compromised by various other factors negatively affecting the quality due to excessive emission levels of air pollutants, such as particulate matter (PM), sulphur dioxide (SO₂), nitrogen dioxide (NO₂) and other toxic gases. Six important locations in the city of Mosul were selected, and the concentrations of the parameters PM2.5, PM10, formaldehyde (HCHO), total volatile organic compounds (TVOC), NO₂ and SO₂ were determined at monthly intervals during the year 2022. The sites were selected both according to their proximity and their specific distance from the direct conflict zone. The aim was to assess the present pollutant levels based on WHO guidelines and to compare the results with previous pre-war studies to understand the long-term war impact on air quality. The results showed that the annual average values of PM2.5, PM10 and NO₂ were above the WHO limits at all locations throughout the year. In contrast, the annual average values of TVOC, HCHO and SO₂ were within the limits in the hot months but exceeded them in the cold months (December to March), which can be attributed to the use of heating material in winter. Two sites revealed higher pollution levels than the others, which can be attributed to their proximity to the devastated areas (conflict zones), high traffic density and a high density of power generators. These factors were further exacerbated by post-war migration from the destroyed and unsafe areas. Thus, in addition to the short-term effects of burning oil fields and sulphur deposits, as well as airborne weapon emissions, the increase in traffic, the use of decentralized power generators, and the higher demand for heating oil, progressive desertification due to deforestation and the destruction of extensive green areas, as well as increasing and unaddressed environmental violations in general, can be held responsible for declining air quality in the urban area. This work should be considered as preliminary work to emphasise the urgent need for conventional air quality monitoring to consolidate air quality data and monitor the effectiveness of different approaches to mitigate war-related air quality deterioration. Possible approaches include the implementation of air purification technologies, the preservation of existing ecosystems, the replacement of fossil energy sources with renewable energy options, proactive and sustainable urban planning and enforcing strict air quality regulations and policies to control and reduce pollution levels. Full article

Nitrogen-based fertilizers are crucial in agriculture for maintaining soil health and increasing crop yields. Soil microorganisms transform nitrogen from fertilizers into ${\mathrm{N}\mathrm{O}}_3^{-}$–N, which is absorbed by crops. However, some nitrogen is converted to nitrous oxide (N₂O), a greenhouse gas with a warming potential about 300-times greater than carbon dioxide (CO₂). Agricultural activities are the main source of N₂O emissions. Monitoring N₂O can enhance soil health and optimize nitrogen fertilizer use, thereby supporting precision agriculture. To achieve this, we developed ionic liquid-gated graphene field-effect transistor (FET) sensors to measure N₂O concentrations in agricultural soil. We first fabricated and tested the electrical characteristics of the sensors. Then, we analyzed their transfer characteristics in our developed N₂O evaluation system using different concentrations of N₂O and air. The sensors demonstrated a negative shift in transfer characteristic curves when exposed to N₂O, with a Dirac point voltage difference of 0.02 V between 1 and 10 ppm N₂O diluted with pure air. These results demonstrate that the ionic liquid-gated graphene FET sensor is a promising device for N₂O detection for agricultural soil applications. Full article

The ever-increasing industrialization of certain areas of the planet combined with the simultaneous degradation of the natural environment are alarming phenomena, especially in the field of human health. The concentration of particulate matter with an aerodynamic diameter of 2.5 μm (PM_2.5) and 10 μm (PM₁₀), nitrogen oxides (NO_x), carbon monoxide (CO), sulfur dioxide (SO₂), and ozone (O₃) needs constant monitoring, as they consist of the main cause for many diseases. Based on the existence of statutory limits from the World Health Organization (WHO) for the concentration of each of the aforementioned air pollutants, it is considered necessary to develop forecasting systems that have the ability to correlate the current meteorological data with the concentrations of the above pollutants. In this work, the attempt to predict air pollutant concentrations in the wider area of Beijing, China, is successfully carried out using artificial neural network (ANN) models. In the frame of a specific work, a significant number of ANNs are developed. For this purpose, an open-access meteorological and air pollution database was used. Finally, a statistical evaluation of the developed prognostic models was carried out. The results showed that ANNs present a remarkable prognostic ability in order to forecast air pollution levels in an urban environment. Full article

Graphene and MXenes have emerged as promising materials for gas sensing applications due to their unique properties and superior performance. This review focuses on the fabrication techniques, applications, and sensing mechanisms of graphene and MXene-based composites in gas sensing. Gas sensors are crucial in various fields, including healthcare, environmental monitoring, and industrial safety, for detecting and monitoring gases such as hydrogen sulfide (H₂S), nitrogen dioxide (NO₂), and ammonia (NH₃). Conventional metal oxides like tin oxide (SnO₂) and zinc oxide (ZnO) have been widely used, but graphene and MXenes offer enhanced sensitivity, selectivity, and response times. Graphene-based sensors can detect low concentrations of gases like H₂S and NH₃, while functionalization can improve their gas-specific selectivity. MXenes, a new class of two-dimensional materials, exhibit high electrical conductivity and tunable surface chemistry, making them suitable for selective and sensitive detection of various gases, including VOCs and humidity. Other materials, such as metal-organic frameworks (MOFs) and conducting polymers, have also shown potential in gas sensing applications, which may be doped into graphene and MXene layers to improve the sensitivity of the sensors. Full article

Natural gas (NG) is commonly used in kitchens, powering stoves, ovens, and other appliances. While it is known for its efficiency and convenience, NG contributes to the release of nitrogen dioxide (NO₂) and can have significant implications for human health. In this study, the importance of the use of NG in kitchens on human exposure to NO₂ was analyzed. An extensive literature review in the field was conducted, and the NO₂ levels were assessed in kitchens with NG cookers in Aveiro and electric cookers in Porto, both in Portugal. Higher levels of NO₂ were found in kitchens in Aveiro, where NO₂ levels outdoors are lower than in Porto. This pollutant can spread to other rooms, especially when ventilation is lacking, which is particularly concerning during colder seasons and at night. As around 70% of the time is spent at home, this can have a significant impact on human exposure to NO₂. Therefore, although Aveiro has low levels of NO₂ outdoors, its population may be exposed to much higher levels of this pollutant than the Porto population, a city with air quality issues, but predominantly using electric cookers. This finding emphasizes the need for the stricter regulation of NG use indoors to protect human health and also suggests a shift in human health protection policies from mere monitoring/control of outdoor air quality to a comprehensive assessment of human exposure, including exposure to indoor air quality. Full article

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2s (PLFs) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM_2.5), 10 μm or less (PM₁₀), and nitrogen dioxide (NO₂), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r < 0.4). Moderate correlation was observed for one PLF unit at the indoor location and two units at the roadside location when measuring PM_2.5, but not for PM₁₀ and NO₂ concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R² values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs. Full article

Nowadays, the study of air quality has become an increasingly prominent field of research, particularly in large urban centers, given its significant impact on human health. In many countries, government departments and research centers use official high-cost scientific instruments to monitor air quality in their regions. Meanwhile, concerned citizens interested in studying the air quality of their local areas often employ low-cost air quality sensors for monitoring purposes. The optimization and evaluation of low-cost sensors have been a field of research by many research groups. This paper presents an extensive study to identify the safe percentage change limits that low-cost electrochemical air quality sensors can have, in order to optimize their measurements. For this work, three low-cost air quality monitoring stations were used, which include an electrochemical sensor for nitrogen dioxide (NO₂) (Alphasense NO2-B43F) and an electrochemical sensor for ozone (O₃) (Alphasense OX-B431). The aim of this work is to explore the variance of the aforementioned sensors and how this variability can be used to optimize the measurements of low-cost electrochemical sensors, closer to real ones. The analysis is conducted by employing diagrams, boxplot and violin curves of the groups of sensors used, with satisfactory results. Full article

Degrading air quality is a matter of concern nowadays, and monitoring air quality helps us keep an eye on it. Air pollution is a pressing global issue with far-reaching impacts on public health and the environment. The need for effective and real-time monitoring systems has become increasingly apparent to combat this growing concern. Here, an innovative air pollution surveillance system (APSS) that leverages Internet of Things (IoT) technology to enable comprehensive and dynamic air quality assessment is introduced. The proposed APMS employs a network of Io enabled sensors strategically deployed across urban and industrial areas. These sensors are equipped to measure various pollutants, including particulate matter (PM2.5 and PM10), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO), and volatile organic compounds (VOCs). Here, a regression model is created to forecast air quality using sensor data while taking into account variables including weather information, traffic patterns, and pollutants. Additionally, air quality categories (such as good, moderate, and harmful) are classified using classification algorithms based on preset thresholds. The IoT architecture facilitates seamless data transmission from these sensors to a centralized cloud-based platform. The developed APSS monitors the air quality using an MQ-135 gas sensor, and the data are shared over a web server using the Internet. An alarm will trigger when the air quality goes below a certain level. Also, the air quality, which is measured in parts per million (PPM), is displayed on the unit connected to it. Furthermore, when the PPM goes beyond a certain level, an alert message is sent to the air pollution control board, which takes preventive measures to control the pollution and also alerts the people, which helps each person in that society save their environment from pollution and have a good air quality environment. Additionally, the APSS offers user-friendly interfaces, accessible through web and mobile applications, to empower citizens with real-time air quality information. The effectiveness of the IoT-based air pollution monitoring system has been validated through successful field trials in urban and industrial environments, and it has the ability to provide real-time data insights and empower stakeholders in promoting environmental sustainability and fostering citizen engagement. Full article

Industrialization, anthropogenic activities, the exhaust of vehicles and exponential population growth have a significant impact on the outdoor air quality of megacities across the world. Karachi is one of the largest cities in Pakistan, South Asia. The dense population, rapid economic growth and unplanned industrial activities have improved the socioeconomic status but also deteriorated the air quality of Karachi. The severe increase in air pollution has become a threat to the local population in terms of their health issues, quality of life and environment. Therefore, it is essential to quantify and monitor the spatiotemporal variation in outdoor air quality parameters. The current study aims to monitor the air quality in four major industrial zones of Karachi for three years (2020–2022). The field data was collected during the periods of post-monsoon and pre-monsoon using the HAZ-SCANNER (HIM-6000) apparatus, which measured outdoor air pollutants such as carbon monoxide (CO), nitrogen oxides (NO₂), sulfur dioxide (SO₂) and particulate matter (PM₁₀, PM_2.5 and TSPM). The data from 24 stations was analyzed using statistical analysis tools to estimate the parameters and Arc GIS to map the spatial variation of each parameter. The result shows that the concentration of particulate matter (TSPM, PM_2.5 and PM₁₀), SO_2, NO₂ and CO values at sampling sites are moderate in the post-monsoon season as compared to the pre-monsoon season due to cyclical monsoon effects and exceed the environmental quality standards. It was also noted that the North Karachi industrial area is at lower risk due to the small-scale industry. The higher levels of air pollutants have numerous health implications and may cause chronic infections. The air pollutant has a severe impact on plant growth and soil. Therefore, it is important to implement local environmental standards regarding outdoor air pollutants to mitigate the adverse impact on human health and economic activities. Full article

Green infrastructure is a nature-based solution that supports sustainable development and restores urban, suburban, and peri-urban environments. Using a multi-scale evaluation, this study explores the impact of the application of green infrastructure, as a form of atmospheric cleansing, on tropospheric nitrogen dioxide. The impacts are not limited to specific green infrastructure treatments nor geographic location and land use type. Using both site-specific stationary air monitoring and coarser resolution satellite derived remote sensing, this study demonstrates the nature-based remediation effect of green infrastructure on nitrogen dioxide concentrations in Southern Ontario, Canada. At these scales, remote sensing and stationary air monitoring observations support the hypothesis that green infrastructure can cleanse the atmosphere by reducing nitrogen dioxide through scavenging by trees and dense vegetation at the neighbourhood level, consistent with the findings from microscale field campaigns. The study showed a clear link between compact, built-up, industrialized areas and higher nitrogen dioxide levels at the mesoscale, particularly notable to the west of the city of Toronto. Nature-based solutions provide an opportunity to address the impacts of urbanization, increase climate resilience, and support healthy urban environments. Full article

Studying carbon dioxide fluxes in wheat fields is becoming increasingly important. The dry semi-humid area in China is an important wheat production area, but the variations in carbon dioxide fluxes in wheat fields and the mechanisms associated with the carbon dioxide flux response to meteorological factors and water-nitrogen management have rarely been studied systematically in this area. Thus, we conducted a monitoring experiment in order to clarify the responses of CO₂-C fluxes to meteorological factors and water-nitrogen management in wheat fields in this dry semi-humid area, and modeled the relationships between CO₂-C fluxes and meteorological factors under different water-nitrogen managements. Four water-nitrogen treatments were tested in wheat fields: rain-fed (no water and nitrogen added), irrigation (150 mm water added), rain-fed plus nitrogen application (225 kg ha⁻¹ nitrogen added), and irrigation plus nitrogen application (150 mm water and 225 kg ha⁻¹ nitrogen added). The CO₂-C fluxes and meteorological indicators were monitored and analyzed, before fitting the relationships between them. The direct and total effects of precipitation, air temperature, and water vapor pressure on CO₂-C fluxes in wheat fields were all positive, and their total effect coefficients were more than 0.7 and significant. Irrigation and nitrogen application increased the CO₂-C fluxes in wheat fields by 6.82–14.52% and 51.59–55.94%, respectively. The fitting results showed that partial least squares regression models of the relationships between meteorological factors and CO₂-C fluxes in wheat fields under different treatments were all effective, with R²Y (cum) and Q² (cum) values around 0.7. Overall, these results suggest that precipitation, air temperature, water vapor pressure, and water and nitrogen addition have positive effects on CO₂-C fluxes from wheat fields in dry semi-humid areas. The partial least squares regression method is also suitable for modeling the relationships between meteorological factors and CO₂-C fluxes. These results may provide a scientific basis for predicting and regulating CO₂-C fluxes in wheat fields in dry semi-humid areas, and provide a methodological reference for ecosystem carbon dioxide flux simulation studies. Full article

Real-time exposure air monitoring is essential to protect the respiratory health of the Malaysian traffic police. However, the data from monitoring stations have been inadequate to provide accurate information about their exposure. This report describes the conceptual design of a wireless exposure indicator system, and then evaluates the field performance of the system by collocation. The study tested the accuracy of particulate matter size 2.5 (PM_2.5), carbon monoxide (CO), and nitrogen dioxide (NO₂) by comparing the measurements from the prototype with the measurements from reference instruments. The field testing found that the data tested were significantly correlated with each other (PM_2.5-rs = 0.207, p = 0.019; NO₂-rs = 0.576, p = 0.02 and CO-rs = 0.545, p = 0.04). The prototype proved to be successful as it can compute and transmit real-time monitoring data on the level of exposure to harmful air. Full article

Greenhouse gas emissions (i.e., carbon dioxide, methane, nitrous oxide) produced by agriculture contribute to global warming and climate change. Various practices followed by farmers in different environmental conditions contribute to the increase in the phenomena, and there is a need for immediate measures. The current study examines the environmental impact of barley production under rain-fed conditions in Cyprus. For this, four different nutrient management scenarios were investigated in order to evaluate the environmental performance of crop production, namely: (1) Nitrogen (20%), Phosphorous (20%), Potassium (10%); (2) Nitrogen (20%), Phosphorous (20%), Potassium (10%) and manure; (3) Nitrogen (25%), Phosphorous (10%), Potassium (0%); and (4) Nitrogen (25%), Phosphorous (10%), Potassium (0%) and manure. Data were collected from two different areas of Cyprus (Nicosia and Larnaca) through on-site visits and questionnaires. Life Cycle Assessment (LCA) was used as a method to quantify environmental impacts which were categorized into six impact categories: (i) acidification potential (AP), (ii) eutrophication potential (EP), (iii) global warming potential (GWP), (iv) ozone depletion potential (ODP), (v) photochemical, ozone creation potential (POCP), and (vi) terrestrial ecotoxicity (TAETP). LCA was used with system boundaries from field to harvest and a functional unit (FU) of one bale of hay. Research results showed that the addition of manure increased values in all impact categories. Comparing scenarios without manure (1 and 3) and with manure (2 and 4), the main process which contributed to GWP was field preparation, which resulted in 3 t CO₂-Eq∙FU⁻¹ and 46.96 t CO₂-Eq∙FU⁻¹, respectively. Furthermore, the highest contribution of sub-processes to GWP (kg CO₂-Eq∙FU⁻¹) was machinery maintenance (scenarios 2 and 4). The potential to reduce environmental impacts from barley and moreover, to mitigate the footprint of the agriculture sector in Cyprus is proposed by changing existing practices such as decreasing fuel consumption by agricultural machinery, and monitoring fertilizing and seeding. Conclusively, the carbon footprint of barley can be decreased through the improvement of nutrient management and cropping practices. Full article

Electrochemical low-cost sensors, suitable for the monitoring of different air quality parameters such as carbon monoxide or nitrogen dioxide levels, are viable tools for creating affordable handheld devices for short-term or dense air quality monitoring networks for long-term measurements and IoT applications. However, most devices that utilize such sensors are based on proprietary hardware and software and, therefore, do not offer users the ability to replace sensors or interact with the hardware, software, and data in a meaningful way. Initiatives that focus on an open framework for air quality monitoring, such as the AirSensEUR project, offer competitive open source alternatives. In this study, we examined the feasibility of the application of such devices. Five AirSensEUR units equipped with chemical sensors were placed next to a reference air quality measuring station in Vienna, Austria. During co-location, concentrations of 0.20 ± 0.06 ppm, 7.14 ± 8.66 ppb, and 17.58 ± 9.90 ppb were measured for CO, NO, and NO₂, respectively. The process of evaluating the performance of the low-cost sensors was carried out and compared to similar studies. Data analysis was carried out with the help of the basic functions in MS Excel. We investigated the linear correlation between the sensor and reference data and thus calculated the coefficient of determination, the average and maximum residuals, and the correlation coefficient. Furthermore, we discuss sensor properties in regard to selectivity and long-term stability. Full article