Air quality nearby road traffic tunnel portals: BTEX monitoring

A monitoring campaign of BTEX （benzene, toluene, ethylbenzene, o- m- and p-xylene） was carried out nearby two tunnel portals in the urban area of Naples with the aim to verify air quality in this kind of urban sites. Sampling was carried out using the active adsorption technique. Sampling time was 1 h. Ambient temperature and traffic flow measurements were carried out during each sampling operation. The results indicate that average benzene concentrations at both sites exceed the limit value of 10 μg/Nm^3 established by the European Community （EC） （Dir. 2000/69）. Concentration levels of other BTEX are relatively high as well. A correlation between BTEX concentration and two wheeler vehicle flow was observed.

Optimization of Air Quality Monitoring Network Using GIS Based Interpolation Techniques

This paper proposes a simple method of optimizing Air Quality Monitoring Network (AQMN) using Geographical Information System (GIS), interpolation techniques and historical data. Existing air quality stations are systematically eliminated and the missing data are filled in using the most appropriate interpolation technique. The interpolated data are then compared with the observed data. Pre-defined performance measures root mean square error (RMSE), mean absolute percentage error (MAPE) and correlation coefficient (r) were used to check the accuracy of the interpolated data. An algorithm was developed in GIS environment and the process was simulated for several sets of measurements conducted in different locations in Riyadh, Saudi Arabia. This methodology proves to be useful to the decision makers to find optimal numbers of stations that are needed without compromising the coverage of the concentrations across the study area.

Air Pollution Concentration Approach to Potential Area Selection of the Air Quality Monitoring Station in Nakhon Ratchasima Municipality, Thailand

The purpose of the study is to generate traffic air information system） to determine a proper zone of AQMS （air analyzed were carbon monoxide （CO）, and nitrogen oxides （NOx） pollution map using mathematical model and GIS （geographic quality monitoring station） in municipality area. The pollutants which can be harmful to people living in the area. The three steps of mapping process were performed under the GIS environment using the existing vehicle emission rates and pollutant dispersion model. First, traffic volume, road network, and the emission rates of road segments varying with types of vehicle were collected from existing data. Second, the pollutant concentrations were calculated by use of CALINE4, a tool with Gaussian dispersion model. The model parameters include emission rate, wind directions and speeds, ambient temperature and observed pollutant concentration, and atmospheric stability during all seasons from the January 1, 2010 to May 31,2011 with regardless the rainy season. This resulted in concentrations at many receptor points along links of the road network. Third, distributions of pollution concentrations were generated by means of the spatial interpolation of those from receptors. The results of pollution raster-based maps are used for determining frequency of violence and combined pollution map. The resulting frequency of violence and intensity concentration will be further integrated to determine a potential area of AQMS. Finally, achieving pollution potential area of AQMS can be located as helpful basic data for efficient traffic and transportation planning.

Air Quality Monitoring and Its Implication on the Environmental Licensing Process in Brazil

In the state of Sao Paulo, Brazil, public policies regarding the air quality aimed at the welfare of the population are strongly dependent on monitoring conducted by the Sao Paulo State Environmental Company (CETESB), which can be influenced by faulty monitors and equipment support and cuts in power supply, among others. A research conducted from 1998 to 2008 indicated that a significant portion of the air quality automatic stations in the state of Sao Paulo did not meet the criterion of representativeness of measurements of PM10, NO2, O3, CO and SO2 concentrations which resulted in the classification of some municipalities as the nonattainment area, a situation evidenced for PM10 and O3 parameters. The network unavailability for each parameter was estimated and compared with the monitoring networks operated in Canada and the UK. This paper discusses the implications of the lack of representativeness of measurements in the environmental licensing process of pollution sources from 2008, when by the effect of state law, municipalities have been qualified according to their air quality nonattainment level.

Investigating the Air Quality Parameters in Louisiana’s Industrial Corridor: A Baton Rouge Case Study

In a local context, sustainable development entails utilizing the current resources—material and immaterial, measurable and immeasurable, popular and unpopular—of the community in a manner that avoids overexploitation and ensures intergenerational equity. This approach prioritizes the safety and health of local citizens, placing communal productivity above corporate profitability. This research aims to assess air quality surrounding 28 chemical industry sites in Baton Rouge, Louisiana, to understand the environmental and health impacts of industrial pollutants, with a focus on environmental justice. Air quality pollutants, including PM2.5, PM10, O3, NO2, CO, and SO2, were monitored for 75 days during the Summer, using the BreezoMeter app. Python, Mapize, and QGIS software technologies were utilized for data analysis and visualization. Findings indicate a reduction in NO2 and CO levels, compared to existing literature. However, the persistent challenge of particulate matter suggests areas for further environmental management efforts. Additionally, the research suggests a significant disparity in air pollution exposure, probably affecting marginalized communities. Although the nature of the study might not fully capture annual pollution trends, the findings highlight the urgent need for the chemical industry to adopt efficient production methods and for policymakers to enhance air quality standards and enforcement, particularly in pollution-sensitive areas. The disproportionate impact of air pollution on vulnerable communities calls for a more inclusive approach to environmental justice, ensuring equitable distribution of clean air benefits and community involvement in pollution management decisions.

Implementation of the Air Quality Monitoring Network at Agadir City in Morocco

Air pollution is a major global issue with widely known harmful effects on human health and the environment. This pollution is a very complex phenomenon given the diversity of pollutants that may be present in the atmosphere. The air quality in urban areas is of a great concern for residents living in cities and represents a current issue that requires an adequate management. So that air quality policy is driven by health concerns. In this paper, we present an overview on the experience of Agadir city to establish the air quality management policy, local authority on the whole have developed a good understanding of air quality in the area. Indeed for several years, efforts have been made to monitor the air quality in this city, this translated by air quality assessment since 2006 using mobile laboratory and fixed station. Our goals in this study were to review the operation of Local Air Quality Management (LAQM) making better use of available resources to improve its outcomes and make recommendations with a view to improving air quality issues. This work highlights the requirement to revise periodically the LAQM for generating priority for air quality issues within local authority and the need to implement the optimizing Air Quality Monitoring Network (AQMN).

Low-Cost Sensors Calibration for Monitoring Air Quality in the Federal District—Brazil

Critical situations that cannot be solved by conventional approaches (traditional air quality monitoring networks), have the possibility of being managed quickly by a wide network of portable systems with sensors. The purpose of this research was to calibrate and validate low-cost sensors. Pilot indoor and outdoor areas, in the central area of Brasilia (Brazil’s capital city) were chosen for corporative performance evaluation of the sensors. The CO at 99.999% volumetric injection method has been used in a gas test box, among two MiCS-5521 (CO/VOC) sensors, one being new and the other one with a short useful life. The number of injections adopted to each volume (from 1 ml to 6 ml) was 10, rising each sensor’s confidence interval mean. A increase of the injected volume (ml) of CO resulted in significant decrease in a resistance (Ohms), as shown by a good inverse relationship on the interaction of these two variables (r = 0.88), with good measurement accuracy, when compared to the manufacturer’s reference datasheet. Finally, a geospatial management system was built for the pollution data measured by the low-cost sensors.

Comprehensive evaluation method of urban air quality statistics based on environmental monitoring data and its application

Air quality monitoring is effective for timely understanding of the current air quality status of a region or city.Currently,the huge volume of environmental monitoring data,which has reasonable real-time performance,provides strong support for in-depth analysis of air pollution characteristics and causes.However,in the era of big data,to meet current demands for fine management of the atmospheric environment,it is important to explore the characteristics and causes of air pollution from multiple aspects for comprehensive and scientific evaluation of air quality.This study reviewed and summarized air quality evaluation methods on the basis of environmental monitoring data statistics during the 13th Five-Year Plan period,and evaluated the level of air pollution in the Beijing-Tianjin-Hebei region and its surrounding areas(i.e.,the“2+26”region)during the period of the three-year action plan to fight air pollution.We suggest that air quality should be comprehensively,deeply,and scientifically evaluated from the aspects of air pollution characteristics,causes,and influences of meteorological conditions and anthropogenic emissions.It is also suggested that a threeyear moving average be introduced as one of the evaluation indexes of long-term change of pollutants.Additionally,both temporal and spatial differences should be considered when removing confounding meteorological factors.

Monitoring Ambient Air Quality in the Carpathian Region of Ukraine

Ivano-Frankivsk oblast is located in the south-western part of Ukraine, close to the geographical center of Europe at the junction of the two major geographic units, the East European Plain and the Eastern Carpathians （the Carpathian region of Ukraine）. Between September 2013 and September 2015, the expert group of the Department of Organic and Analytical Chemistry of Vasyl Stefanyk Precarpathian National University conducted the mobile monitoring of air cleanliness in Ivano-Frankivsk region; the authors monitored the level of air contamination with seven gases： carbon monoxide and dioxide, sulfur dioxide, nitrogen dioxide, hydrogen sulfide, ammonia, formaldehyde, beta-particles, and gamma radiation. For this purpose, there were used six automatic analyzers ＂Dozor-C-P＂, the formaldehyde Gas Analyzer ＂MIC-98170＂, and the radiometer ＂TERRA＂. The monitoring resulted in the making of three maps of Ivano-Frankivsk region, on which the average levels of concentration of three particular gases （CO2, SO2, and CH20） throughout all the districts of the oblast were marked. There was registered the excess of CH20 limits--the consequences of the presence of the chipboard and wood-fiber production, for which formaldehyde is used as a raw material. Also there was observed the excess of SO2 in the air caused by gas fumes from vehicles and thermal power stations.

The Application of Pearson Correlational Analysis Method in Air Quality Analysis of Beijing-Tianjin-Hebei Region

Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July 23 of 2014, this article adopted Pearson correlation coefficient method to determine the relevance among each pollutant of these cities with the help of SPSS. The results showed that such three leading indexes as SO2, PM10 and PM2.5 had strong correlation in Beijing, Tianjin and main cities of Hebei. Finally, some suggestions and preventive measures for the cooperative governance of air pollution in Beijing-Tianjin-Hebei Region were put forward, hoping this can help them.

Multi-sensing paradigm based urban air quality monitoring and hazardous gas source analyzing:a review

Effectively monitoring urban air quality,and analyzing the source terms of the main atmospheric pollutants is important for public authorities to take air quality management actions.Previous works,such as long-term obser-vations by monitoring stations,cannot provide customized data services and in-time emergency response under urgent situations(gas leakage incidents).Therefore,we first review the up-to-date approaches(often machine learning and optimization methods)with respect to urban air quality monitoring and hazardous gas source anal-ysis.To bridge the gap between present solutions and practical requirements,we design a conceptual framework,namely MAsmed(Multi-Agents for sensing,monitoring,estimating and determining),to provide fine-grained concentration maps,customized data services,and on-demand emergency management.In this framework,we leverage the hybrid design of wireless sensor networks(WSNs)and mobile crowdsensing(MCS)to sense urban air quality and relevant data(e.g.traffic data,meteorological data,etc.);Using the sensed data,we can create a fine-grained air quality map for the authorities and relevant stakeholders,and provide on-demand source term estimation and source searching methods to estimate,seek,and determine the sources,thereby aiding decision-makers in emergency response(e.g.for evacuation).In this paper,we also identify several potential opportunities for future research.

Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

Environmental sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environment particularlyby highly populated countries like India. Due to increased population, thenumber of vehicles also continues to increase. Each vehicle has its individualemission rate;however, the issue arises when the emission rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop predictionapproaches to monitor and control pollution using real time data. With thedevelopment of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm shift in how environmental data are employed forsustainable cities and societies, especially by applying intelligent algorithms.In this view, this study develops an optimal AI based air quality prediction andclassification (OAI-AQPC) model in big data environment. For handling bigdata from environmental monitoring, Hadoop MapReduce tool is employed.In addition, a predictive model is built using the hybridization of ARIMAand neural network (NN) called ARIMA-NN to predict the pollution level.For improving the performance of the ARIMA-NN algorithm, the parametertuning process takes place using oppositional swallow swarm optimization(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system (ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experimental analysis is performed for highlighting the betterprediction performance of the proposed ARIMA-NN method. The obtainedoutcomes pointed out the enhanced outcomes of the proposed OAI-AQPCtechnique over the recent state of art techniques.

Research on Decision Support System (DSS) of Atmospheric Environment Management in Anhui Province Based on Air Quality Forecasting

With the atmospheric stereoscopic monitoring, air quality forecasting and decision of environment management as the main line, and comprehensive management system as the guidance, five platforms including infrastructure, technological support, monitoring and early monitoring, decision support and information services were established. These platforms have 15 subsystems, including stereoscopic monitoring network, visual business consultation, high-performance computing environment, comprehensive management of atmospheric data, emission inventories of pollu-tion sources, evaluation tools of atmospheric models, monitoring and management of air pollution, forecasting and early warning of air quality, diag-nostic analysis of atmospheric environment, tracking of air pollution sources, emergency management of air pollution, conformity management of air quality, comprehensive display of information, releasing of information to external networks, and releasing of information by mobile networks. The decision support system （DSS） of atmospheric environment management could realize an integration business system of 11 air quality forecast - heavy pollution weather warning - diagnosis of pollution causes （dynamic analysis of pollution sources） -air quality conformity planning （air pollu-tion emergency management） -evaluation of forecasting and warning results （evaluation pf management measures） -air quality forecasting＂ and provide the technical support for the prevention and control of atmosphere pollution in Anhui province.

A methodological framework for improving air quality monitoring network layout.Applications to environment management

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network(AQMN).It requires to be constituted by a minimum and reliable number of measurement sites.Nevertheless,the AQMN efficiency should be assessed over time,as a consequence of the possible emergence of new emission sources of air pollutants,which could lead to variations on their spatial distribution within the target area.PM_(10)particles data monitored by the Community of Madrid's(Spain)AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance.The annual spatial distribution of average PM_(10)levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system(GIS),and the percentage of similarity between both postulates was quantified using simple linear regression(>95%).As one innovative tool of this study,the practical application of the proposed methodology was validated using PM_(10)particles data measured by AQMN during 2007 and 2018,reaching a similitude degree higher than 95%.The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN,it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations,which could help to tackle efforts to improve the air quality management.

A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013–2016

In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%～46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0～ 75 μg/m^3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%～62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy.

The Representativeness of Air Quality Monitoring Sites in the Urban Areas of a Mountainous City

Lanzhou is a typical mountainous city with severe air pollution in northwestern China. This study uses hourly observational data of air pollutants at five air quality monitoring sites in Lanzhou from July to December 2015 to discuss data quality control and the representativeness of the monitoring sites(four urban sites and one suburban site). A fuzzy matrix is applied to study primary air pollutants. The results show that of the six routinely monitored pollutants,the primary pollutant is PM_10 during the study period. Based on lag correlation analysis and one-way analysis of variance, it is concluded that there are redundant observations at the four urban sites for the timely diffusion and transport of air pollutants from the same general area. The coefficient of divergence(COD) method is then used to evaluate the spatial distribution differences, and the primary air pollutant PM_10 shows differences at each site. COD can be used as a positive indicator to describe site representativeness. To evaluate the overall air pollution in the valley, correlation analysis is performed between the PM_10 concentration retrieved from aerosol optical depth satellite data and the concentration from the four urban monitoring sites. Among these, the correlation between the workers' hospital site data and the retrieval data is the highest, passing the 90% confidence level. A new representative evaluation model for air quality monitoring sites, R_s = 0.77 COD + 0.23R_(retrieval), is established by using COD and correlation coefficients between routine observations and satellite retrieval products. From this model, it can be concluded that the biological products institute site in Lanzhou is the most representative site for the evaluation of air pollution out of the four urban air quality monitoring sites from July to December 2015.

An Optical Fiber Sensor Probe Using a PMMA/CPR Coated Bent Optical Fiber as a Transducer for Monitoring Trace Ammonia

Ammonia sensors have broad spectrum of applications for industrial process control as well as for environ-mental monitoring. An optical fiber ammonia sensor probe has been developed by using a bent optical fiber having dual poly(methyl methacrylate) (PMMA)/chlorophenol red (CPR) coatings as a transducer. This sen-sor probe was tested for monitoring trace ammonia in gas samples using air as sample matrix. The reaction of ammonia with CPR causes a color change of the reagent, which was detected by using fiber optic evanes-cent wave absorption spectrometry as a sensing signal. By adopting a dual layer coating structure, the sensor probe has faster response compared to a sensor using a broadly accepted sensing reagent-immobilized poly-mer coating structure. The sensor developed in this work is sensitive, has a detection limit of 2.7 ppb NH3 in air, which is the most sensitive among the reported optical fiber ammonia sensors to the best knowledge of the authors. The sensor is also reversible and has a response time of 25 minutes. The features of high sensi-tivity, reversibility and reasonable response time make this sensor technique very attractive for air quality monitoring.

A Comparison of Airborne Formaldehyde Field Measurements Collected in an Anatomic Pathology Laboratory

Environmental monitoring of airborne formaldehyde (FA) using sensitive methodologies is fundamental to prevent health risks. The objective of this study was to compare three different FA monitoring methods during the daily activities of an anatomic pathology laboratory. Daily eight-hour measurements deriving from Radiello® passive diffusive samplers (PDS), NEMo XT continuous optical sensor (COS), and multi-gas 1512 photoacoustic monitor (MPM) were simultaneously compared over a period of 14 working days. Given the different daily distributions of the measurements performed by the three devices, all measurements were time-aligned for comparison purposes. The 95% limit of agreement (LOA) method was applied to estimate the degree of concordance of each device with respect to the others. Formaldehyde arithmetic mean measured using PDS was 32.6 ± 10.4 ppb (range: 19.8 - 62.7). The simultaneous measures performed by COS and MPM were respectively 42.4 ± 44.8 ppb (range: 7.0 - 175.0) and 189.0 ± 163.7 ppb (range: 40.0 - 2895.4). The MPM geometric mean (171.3 ppb) was approximately five times higher than those derived from COS (32.3 ppb) and PDS (31.4 ppb). The results of the LOA method applied to log-transformed FA data showed the same systematic discrepancies between MPM and the other two devices. A good agreement between PDS and COS could lead to a tailored approach according to the individual specificity of these techniques. This tool may be useful for accurately assessing the risk of FA exposure among healthcare workers. However, the limited specificity of the MPM does not support its use as a monitoring method for FA in the workplace.

Ultrasensitive Indium Phosphide Nanomembrane Wearable Gas Sensors

Air quality is deteriorating due to continuing urbanization and industrialization.In particular,nitrogen dioxide(NO_(2))is a biologically and environmentally hazardous byproduct from fuel combustion that is ubiquitous in urban life.To address this issue,we report a high-performance flexible indium phosphide nanomembrane NO_(2)sensor for real-time air quality monitoring.An ultralow limit of detection of~200 ppt and a fast response have been achieved with this device by optimizing the film thickness and doping concentration during indium phosphide epitaxy.By varying the film thickness,a dynamic range of values for NO_(2)detection from parts per trillion(ppt)to parts per million(ppm)level have also been demonstrated under low bias voltage and at room temperature without additional light activation.Flexibility measurements show an adequately stable response after repeated bending.On-site testing of the sensor in a residential kitchen shows that NO_(2)concentration from the gas stove emission could exceed the NO_(2)Time Weighted Average limit,i.e.,200 ppb,highlighting the significance of real-time monitoring.Critically,the indium phosphide nanomembrane sensor element cost is estimated at<0.1 US$due to the miniatured size,nanoscale thickness,and ease of fabrication.With these superior performance characteristics,low cost,and real-world applicability,our indium phosphide nanomembrane sensors offer a promising solution for a variety of air quality monitoring applications.

Evaluation of health benefit using Ben MAP-CE with an integrated scheme of model and monitor data during Guangzhou Asian Games

Guangzhou is the capital and largest city（land area：7287 km2）of Guangdong province in South China.The air quality in Guangzhou typically worsens in November due to unfavorable meteorological conditions for pollutant dispersion.During the Guangzhou Asian Games in November 2010,the Guangzhou government carried out a number of emission control measures that significantly improved the air quality.In this paper,we estimated the acute health outcome changes related to the air quality improvement during the 2010 Guangzhou Asian Games using a next-generation,fully-integrated assessment system for air quality and health benefits.This advanced system generates air quality data by fusing model and monitoring data instead of using monitoring data alone,which provides more reliable results.The air quality estimates retain the spatial distribution of model results while calibrating the value with observations.The results show that the mean PM2.5concentration in November 2010 decreased by 3.5μg/m^3 compared to that in 2009 due to the emission control measures.From the analysis,we estimate that the air quality improvement avoided 106 premature deaths,1869 cases of hospital admission,and 20,026 cases of outpatient visits.The overall cost benefit of the improved air quality is estimated to be 165 million CNY,with the avoided premature death contributing 90%of this figure.The research demonstrates that Ben MAP-CE is capable of assessing the health and cost benefits of air pollution control for sound policy making.