Real-time air pollution monitoring with sensors on city bus

This paper presents an experimental study on real-time air pollution monitoring using wireless sensors on public transport vehicles.The study is part of the GreenIoT project in Sweden,which utilizes Internet-of-Things to measure air pollution level in the city center of Uppsala.Through deploying low-cost wireless sensors,it is possible to obtain more fine-grained and real-time air pollution levels at different locations.The sensors on public transport vehicles complement the readings from stationary sensors and the only ground level monitoring station in Uppsala.The paper describes the deployment of wireless sensors on Uppsala buses and the integration of the mobile sensor network with the GreenIoT testbed.Extensive experiments have been conducted to evaluate the communication quality and data quality of the system.

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.

Pollution monitoring of marine organisms grown in the Zhoushan Sea of China

The sustainable regeneration of the biggest fishery resource in the Zhoushan Sea area of China has been adversely affected in recent years. Wastewater discharged into the marine ecosystem is the main source of pollution. Affected organisms such as hairtail prawn, jellyfish, crab, laver and kelp were monitored, and the contributions and fluxes of three sort of pollutants(oils, Cr and phenol) from the expansion of rural enterprises in the Yangtze River valley, the Qiantang River valley, the Ningbo coastal area and the Zhoushan islands were calculated. More than 16 chemical pollutants were jointly responsible for the decrease in the yield and quality of marine organisms. Furthermore, combined contamination effects and their joint toxicity differed between summer and winter, because they were varied with different temperature, salinity, pH and E h.

Marine environmental quality, pollution monitoring and environmental management

Chinese government has adopted a series of management measures to prevent and manage marine pollution and to protect ocean bio resources and ecosystem. The key points of Chinese marine environmental quality status, pollution monitoring and environmental management since 1980' were discussed in this paper. Those included the investigations of Chinese coast environmental quality, monitoring techniques and standards, as well as the marine environmental management measures. Recent status of marine environmental pollution and the monitoring network in China were also introduced.

Study on the Monitoring Malfunction of Water Pollution during Drought or Flood Period and Low-carbon and High-value Methodology--A Case Study of the Correlation Test of Water,Soil and Gas Pollution in Xiangxiang County

Based on the low-carbon and high-value methodology of chemical ecology and chemical informatics,combining theory and methods,taking saving,environmental protection,low carbon,high production,high value and circulation as values and aims,the relationship between human and land as a basis,ecosystem as a center,overall control as a goal and agricultural ecological engineering as a mean,environmental pollution detection,as one of bottlenecks for agricultural products and food security,should be solved firstly;through the field survey in dry years from 2009 to 2010 when drought and flood were frequent and the frequency of drought was higher than that of flood,plus the determination of surface water flow and water quantity in a small typical river basin,the correlation of local water,soil and gas in the county could be found,and the transfer of monitoring focus from water environment to atmospheric environment was possible and necessary.The study would promote the quantitative research on the correlation among water,soil and gas,and the results were in accordance with the conclusions of related studies.

Gaussian Support Vector Machine Algorithm Based Air Pollution Prediction

Air pollution is one of the major concerns considering detriments to human health.This type of pollution leads to several health problems for humans,such as asthma,heart issues,skin diseases,bronchitis,lung cancer,and throat and eye infections.Air pollution also poses serious issues to the planet.Pollution from the vehicle industry is the cause of greenhouse effect and CO2 emissions.Thus,real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary actions.The monitoring process has become efficient and dynamic with the advancement of the Internet of things and wireless sensor networks.Localization is the main issue in WSNs;if the sensor node location is unknown,then coverage and power and routing are not optimal.This study concentrates on localization-based air pollution prediction systems for real-time monitoring of smart cities.These systems comprise two phases considering the prediction as heavy or light traffic area using the Gaussian support vector machine algorithm based on the air pollutants,such as PM2.5 particulate matter,PM10,nitrogen dioxide(NO2),carbon monoxide(CO),ozone(O3),and sulfur dioxide(SO2).The sensor nodes are localized on the basis of the predicted area using the meta-heuristic algorithms called fast correlation-based elephant herding optimization.The dataset is divided into training and testing parts based on 10 cross-validations.The evaluation on predicting the air pollutant for localization is performed with the training dataset.Mean error prediction in localizing nodes is 9.83 which is lesser than existing solutions and accuracy is 95%.

Air Pollution in the Gulf of Mexico

An integral analysis of Air Pollution in the Gulf of Mexico was made considering pollutants emissions assessment and diagnosis;air pollution monitoring;and modeling of air pollution dispersion. Combustion sources considered in this work were: thermoelectric power plants and open flares;and pollutants considered were sulfur dioxide, nitrogen dioxides, particulate matter (PM10 and PM2.5), Total suspended particles (TSP) and carbon monoxide (CO). This study made evident a lack of more recent information and a homogenization in emissions factors in order to know the conditions of air pollution in the Gulf of Mexico in a more reliable way.

Environmental monitoring and fuzzy synthetic evaluation of municipal solid waste transfer stations in Beijing in 2001-2006

Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management system,the authors measured the existing environmental quality at five MSW TSs.Discharged wastewater,air,and noise were monitored and assayed at the five TSs in Beijing in 2001-2006 during rainy seasons(RSs)and dry seasons(DSs).Except Ammonia(NH_3)and hydrogen sulfide(H_2S),the analytical results of...

Development and experience in the monitoring,assessment and control of environmentalpollutants in Hong Kong

The late start of environmental protection in Hong Kong was discussed in the light of problems encountered during the development of environmental protection legislation in Hong Kong for the past 20 years. The collaboration in monitoring and assessment of environmental pollutants between the University of Hong Kong and various governments were descrbed in parallel with the progress in environmental protection in Hong Kong. The developments of new analytical techniques for environmental monitoring and analysis is given and their application in environmental control described. The joint projects in assessment and control of environmental pollutants carried out in collaboration with local industries and other organizations within and without the university are given and discussed. The problems and possible solution facing Hong Kong in development control equipment for small scale industries are discussed and areas of development identified. The development and experience in the monitoring assessment and control of environmental pollutants in Hong Kong are summarized and areas of difficulties are illustrated.

Particulate matter pollution in Kunshan High-Tech zone： Source apportionment with trace elements, plume evolution and its monitoring

Particulate matter （PM} in the Kunshan High-Tech zone is studied during a three-month campaign. PM and trace elements are measured by the online pollution monitoring, forecast-warning and source term retrieval system AS3. Hourly measured concentrations of PM10, PM2.5 and 16 trace elements in the PM2.5 section （Ca, Pb, Cu, C1, V, Cr, Fe, Ti, Mn, Ni, Zn, Ga, As, Se, Sr, Ba） are focused. Source apportionment of trace elements by Positive Matrix Factorization modeling indicates that there are five major sources, including dust, industrial processing, traffic, combustion, and sea salt with contribution rate of 23.68%, 21.66%, 14.30%, 22.03%, and 6.89%, respectively. Prediction ofptume dispersion from concrete plant and traffic emissions shows that PM20 pollution of concrete plant is three orders of magnitude more than that of the traffic. The influence range can extend to more than 3 km in 1 hr. Because the footprint of the industrial plumes is constantly moving according to the local meteorological conditions, the fixed monitoring sites scattered in a few hundred meters haven＇t captured the heaviest pollution plume at the local scale of a few km2. As a more intensive monitoring network is not operationally possible, the use of online modeling gives accurate and quantitative information of plume location, which increases the spatial pollution monitoring capacity and improves the understanding of measurement data. These results indicate that the development of the AS3 system, which combines monitoring equipment and air pollution modeling systems, is beneficial to the real-time pollution monitoring in the industrial zone.

Bacteriophages in water pollution control:Advantages and limitations

Wastewater is a breeding ground for many pathogens,which may pose a threat to human health through various water transmission pathways.Therefore,a simple and effective method is urgently required to monitor and treat wastewater.As bacterial viruses,bacteriophages(phages)are the most widely distributed and abundant organisms in the biosphere.Owing to their capacity to specifically infect bacterial hosts,they have recently been used as novel tools in water pollution control.The purpose of this review is to summarize and evaluate the roles of phages in monitoring pathogens,tracking pollution sources,treating pathogenic bacteria,infecting bloom-forming cyanobacteria,and controlling bulking sludge and biofilm pollution in wastewater treatment systems.We also discuss the limitations of phage usage in water pollution control,including phage-mediated horizontal gene transfer,the evolution of bacterial resistance,and phage concentration decrease.This review provides an integrated outlook on the use of phages in water pollution control.

Study of cadmium(Cd)-induced oxidative stress in Eisenia fetida based on mathematical modelling

As a sensitive biological indicator,earthworms are widely used to monitor various pollutants of soil and provide an early warning for soil pollution.However,because many indices are involved in the exposure-induced oxidative stress response,practical applications of these indices are quite inconvenient.Therefore,it is appropriate to investigate the key monitoring index for use in early warning and pollution monitoring.Using Eisenia fetida as an experimental model in an indoor simulation experiment,the mathematical modelling of the effect on oxidative stress in earthworms under cadmium(Cd)stress was studied.The test lasted 40 d,with the removal of one earthworm every 10 d.The Cd2+concentration gradient was set as 0,1,10,20,100,200,400,and 800 mg kg^(-1) dry weight.The earthworms were divided into two sections from the clitellum for the determination of total protein(TP)and peroxidase(POD),superoxide dismutase(SOD),glutathione-S-transferase(GST),glutathione peroxidase(GPX),catalase(CAT),malondialdehyde(MDA),and acetylcholinesterase(AChE)activities.Results showed that POD was the key index of oxidative stress in head tissues after 10 d of exposure,TP was the key index at 20 d,and POD became the key index again at 30 and 40 d.By contrast,in tail tissues,MDA and SOD were the key indices at an exposure time of 10 d,GPX at 20 d,CAT and TP at 30 d,and POD and MDA at 40 d.These results contribute to establishing a scientific method for ecotoxicological diagnosis and revealing the mechanism of soil Cd toxicity.

Emerging challenges of ozone impacts on asian plants:actions are needed to protect ecosystem health

Context:Ozone concentrations near the land surface are rising in Asia while they are declining or stagnating in Europe and North America.Ozone is the most widespread air pollutant negatively affecting vegetation,and its increased concentrations pose a major threat to food quality and production and other ecosystem services in Asia.Method:In this review,we provide an overview of scientific challenges in the impacts of ozone pollution on Asian vegetation,and synthesize the challenges toward mitigation of the impacts.Result:We argue that new policy initiatives need to seek both reduction of ozone levels and enhancement of plant tolerance to ozone to maintain food quality and ensure food supplies.Conclusion:The scientific advancements must be transferred to actions by two types of institutions:a)environmental agencies for reducing ozone levels and b)agricultural research institutions for enhancing plant tolerance to ozone.In connecting the scientific advancements with the institutional actions,scientists in Asian countries should play the key role taking advantages of interdisciplinary and international collaborations.

Variations in traffic-related polycyclic aromatic hydrocarbons in PM2.5 in Kanazawa, Japan, after the implementation of a new vehicle emission regulation

A three-year sampling campaign was conducted at a roadside air pollution monitoring station in the urban area of Kanazawa, Japan. Due to a new emission regulation, PAHs levels decreased over the sampling campaign, exhibiting values of 706 ± 413 pg/m^(3) in 2017, 559 ±384 pg/m^(3) in 2018, and 473 ± 234 pg/m^(3) in 2019. In each year, similar seasonal variations in PAHs levels were observed, with higher levels observed in winter and lower levels in summer. Among the PAHs isomer ratios, we observed that the ratio of benzo[b]fluoranthene(BbF) and benzo[k]fluoranthene(BkF), [Bb F]/([BbF] + [BkF]), and the ratio of indeno[1,2,3-cd]pyrene(IDP) and benzo[ghi]perylene(BgPe), [IDP]/([BgPe] + [IDP]), showed stability over the sampling campaign and were less affected by the new emission regulation, seasonal variations, and regional characteristics. When using the combined ratio ranges of 0.66-0.80([Bb F]/[BbF] + [BkF]) and 0.26-0.49([IDP]/[Bg Pe] + [IDP]), traffic emissions were clearly distinguished from other PAHs emission sources. Principal component analysis(PCA) and positive matrix factorization(PMF) were also performed to further analyse the characteristics of traffic-related PAHs. Overall, this study affirmed the effectiveness of the new emission regulation in the reduction of PAHs emissions and provided a combined range for identifying PAHs traffic emission sources.