Real time remote monitoring of air pollutants and their online transmission to the web using internet protocol

Recent advances in both information and sensor technologies have enabled the development of Real Time Remote Monitoring (RTRM) capabilities for environmental management. An online and real time remote monitoring system for air pollution has been designed and installed at a traffic police station at Punjagutta in Hyderabad, India. The system is optimized using electrochemical sensors and a real time particulate matter analyzer. The system also monitors meteorological parameters such as temperature, humidity, rainfall, barometric pressure, wind speed and wind direction. The system periodically monitors both pollution and meteorological parameters at pre- programmed intervals of hr during peak periods and 1 hr during non peak periods of the day and continuously uploads to a predestinated web site (www.appcb.org/home.htm) using File Transfer Protocol. The web site renders a quick, simple and graphical display of air pollution levels and meteorological parameters and their significance to humans. The present paper highlights design considerations of a pollution monitoring system, system hardware and software requirements and practical limitations and future directions for real time remote monitoring of air pollution.     

Combining a road pollution dispersion model with GIS to determine carbon monoxide concentration in Tennessee

The purpose of this paper is to develop an air pollution model that is independent from pollution monitoring sites and highly accurate through space and time. Total carbon monoxide concentration is computed with the use of traffic flow data, vehicle speed and dimensions, emission rates, wind speed, and temperature. The data are interpolated using a geographic information system universal kriging technique, and the end results produce state level air pollution maps with high local accuracy. The model is validated against Environment Protection Agency (EPA) pollution data. Overall, the model has 71 % agreement with EPA, overestimating values of carbon monoxide for less than 1 ppm. The model has three advantages over already assessed air pollution models. First, it is completely independent of any air pollution monitoring stations; thus, possible temporary or permanent unreliability or lack of the data is avoided. Second, being based on a 5,710 traffic count network, the problem of remote places coverage is avoided. Third, it is based on a straightforward equation, where minimal preprocessing of traffic and climatic data is required.     

北京市大气气态汞变化特征

采用Tekran 2537X大气汞分析仪在线测量北京市城区大气中气态元素汞(GEM,简称大气汞) 浓度,研究大气汞浓度随不同气象条件的变化特征。通过分析2016年10月—2017年9月大气汞监测数据发现,该监测点全年大气汞浓度为0.48～16.25 ng/m³,均值为(3.41±1.79)ng/m³。春季、夏季、秋季和冬季大气汞浓度均值依次为2.93 、2.95、4.27、3.37 ng/m³,其中,秋季大气汞浓度明显高于其他季节 。秋季大气汞浓度显著偏高可能由不利的大气扩散条件导致。大气汞夜间浓度显著高于白天浓度。同时,将大气汞与SO₂、CO及PM_2.5进行相关性分析,发现大气汞浓度变化趋势与SO₂、CO和PM_2.5呈显著正相关。结合风向和风速进行污染来源分析,得到该点位大气汞在西南和东北方向上受人为排放源影响较大。污染源类型分析表明,冬季大气汞与CO同源性强,主要来自本地供暖用煤。     

The Comparison of Lagrangian and Gaussian Models in Predicting of Air Pollution Emission Using Experimental Study,a Case Study: Ammonia Emission

Ammonia, as a colorless gas with a sharp odor, is considered as one of the created odors in the composting and landfill of solid waste. We used experimental data to study the robustness of AERMOD and the forward Lagrangian stochastic (FLS) in predicting ammonia emission in short range. The study area was Kahrizak landfill and composting plants, Tehran, Iran. The boundary layer parameters for the FLS were calculated on the basis of mean values of temperature, wind speed, and direction. While, the boundary layers of AERMOD were computed on the basis of exact meteorological data. The results depicted that AERMOD prediction at distances less than 1000 m from the sources and the locations inside the sources were poor. However, the results of FLS indicated more agreement with the field measurement, which the coefficient of determination was 0.83. Both models predicted, in the distance of 2000 m from the source, the ammonia concentration would be insignificant.     

Speciation and sources of atmospheric aerosols in a highly industrialised emerging mega-city in central China

Monitoring air quality in large urban agglomerations is the key to the prevention of air pollution-related problems in emerging mega-cities. The city of Wuhan is a highly industrialised city with >9 million inhabitants in Central China. Simultaneous PM10 sampling was performed during 1 year at one urban and one industrial site. Mean PM10 daily levels (156 microg m(-3) at the urban site and 197 microg m(-3) at the industrial hotspot) exceed the US-EPA or EU annual limit values by 3-4 times. A detailed study of daily speciation showed that the mean chemical composition of PM10 presents minimal differences between peak and low PM episodes. This implies that PM10 aerosols in the study area result from local emissions, and air quality management and abatement strategies in Wuhan should thus focus on local anthropogenic sources. The levels of some elements of environmental concern are relatively high (409-615 ngPb m(-3), 66-70 ngAs m(-3), 116-227 ngMn m(-3), 10-12 ngCd m(-3)) due to industrial, but also urban emissions. Principal component analysis identified a mineral source (probably cement and steel manufacture) and smelting as the main contributors to PM10 levels at the industrial site (34%), followed by a coal fired power plant (20%) and the anthropogenic regional background (16%). At the urban site the major PM10 source is a mixed coal combustion source (31%), followed by the anthropogenic regional background (28%) and traffic (16%).     

Soil Water Content Estimated by Support Vector Machine for the Assessment of Shallow Landslides Triggering: the Role of Antecedent Meteorological Conditions

Soil water content is a key parameter for representing water dynamics in soils. Its prediction is fundamental for different practical applications, such as identifying shallow landslides triggering. Support vector machine (SVM) is a machine learning technique, which can be used to predict the temporal trend of a quantity since training from past data. SVM was applied to a test slope of Oltrepò Pavese (northern Italy), where meteorological parameters coupled with soil water content at different depths (0.2, 0.4, 0.6, 1.0, 1.2, 1.4 m) were measured. Two SVM models were developed for water content assessment: (i) model 1, considering rainfall amount, air temperature, air humidity, net solar radiation, and wind speed; (ii) model 2, considering the same predictors of model 1 together with antecedent condition parameters (cumulated rainfall of 7, 30, and 60 days; mean air temperature of 7, 30, and 60 days). SVM model 2 showed significantly higher satisfactory results than model 1, for both training and test phases and for all the considered soil levels. SVM models trends were implemented in a methodology of slope safety factor assessment. For a real event occurred in the tested slope, the triggering time was correctly predicted using data estimated by SVM model based on antecedent meteorological conditions. This confirms the necessity of including these predictors for building a SVM technique able to estimate correctly soil moisture dynamics in time. The results of this paper show a promising potential application of the SVM methodologies for modeling soil moisture required in slope stability analysis.     

Polycyclic aromatic hydrocarbons (PAHs) in the air of Chinese cities

Polycyclic aromatic hydrocarbons (PAHs) were determined in the air of 37 cities and 3 rural locations across China during the winter, spring, summer and autumn of 2005, using polyurethane foam (PUF) disks as passive air samplers (PAS). Winter and autumn concentrations in cities exceeded spring and summer values. Concentrations were amongst the highest in the world; seasonally averaged autumn/winter values in some cities in the north and north-west of China exceeded proposed European Union air quality standards. Several factors, acting in combination, influenced air concentrations. A significant negative correlation was found between average annual city concentrations and the annual average temperature, while winter time PAH concentrations correlated with estimated coal consumption. The highest total PAH concentrations and loadings of high molecular weight compounds generally occurred in major cities located on higher land (500-2000 m), where relatively cold winters and higher coal consumption occurs. Lower values occurred in cities located in the south and east China and along the coastal regions. Molecular markers indicated incomplete combustion of fossil fuels dominated the urban air and gave evidence for photo-decomposition of selected compounds.     

支撑京津冀区域大气污染联防联控的大气监测体系构建

京津冀区域已成为全国大气污染最严重的地区之一,并且呈现出明显的区域性污染特征,加强区域间的环境合作,实施区域联防联控是解决京津冀区域大气污染问题的有效手段。对照《生态环境监测网络建设方案》的要求,目前京津冀区域大气监测体系还存在着监测网络不健全、监测项目覆盖不全面、监测新技术应用不足、质控体系不完善、信息产品供给与公众需求有差距等问题,与京津冀区域大气污染联防联控的要求不相适应。为全面提升京津冀区域大气监测体系对区域联防联控的技术支撑能力,亟需进一步完善京津冀区域的监测网络,增设传输研究、污染监控等特殊监测点位;逐步拓展监测项目,开展颗粒物化学组分和O_3前体物监测;加快遥感监测等立体监测技术在大气监测中的应用,全面分析污染物时空分布特征与传输规律;加强空气质量预报预警能力建设,为重污染天气应对提供技术支持;规范监测事权上收后的全过程质控体系,建立颗粒物标准方法比对和O_3量值传递质控机制;构建环境监测大数据平台,加强数据分析应用与信息公开。     

Suitability of selected bioindicators of atmospheric pollution in the industrialised region of Ostrava,Upper Silesia,Czech Republic

This study is a continuation of our preceding research identifying suitable environmental samples for the tracing of atmospheric pollution in industrial areas. Three additional types of environmental samples were used to characterise contamination sources in the industrial area of Ostrava city, Czech Republic. The region is known for its extensive metallurgical and mining activities. Fingerprinting of stable Pb isotopes was applied to distinguish individual sources of anthropogenic Pb. A wide range of ²⁰⁶Pb/²⁰⁷Pb ratios was observed in the investigated samples: ²⁰⁶Pb/²⁰⁷Pb = 1.168–1.198 in mosses; ²⁰⁶Pb/²⁰⁷Pb = 1.167–1.215 in soils and ²⁰⁶Pb/²⁰⁷Pb = 1.158–1.184 in tree cores. Black and brown coal combustion, as well as metallurgical activities, is the two main sources of pollution in the area. Fossil fuel burning in industry and households seems to be a stronger source of Pb emissions than from the metallurgical industry. Concentration analyses of tree rings showed that a significant increase in As concentrations occurred between 1999 and 2016 (from 0.38 mg kg^?1 to 13.8 mg kg^?1). This shift corresponds to the use of brown coal from Bílina, Czech Republic, with an increased As concentration. The burning of low-quality fuels in households remains a problem in the area, as small ground sources have a greater influence on the air quality than do industrial sources.     

Seasonal evaluation and spatial variability of suspended particulate matter in the vicinity of a large coal-fired power station in India—A case study

Coal combustion in the power sector gives rise to the emission of primary and secondary particulate pollutants. Since the emission of pollutants depends on coal quality and combustion technology, and given that transport, transformation and deposition of contaminants depend on regional climatic conditions, specific studies for the power stations is needed to evaluate their environmental impacts. Monitoring of ambient respirable suspended particulate matter (RSPM) and suspended particulate matter (SPM) levels around a large coal-fired power station in India was carried out. The specific objectives were the determination of spatial and seasonal variability in RSPM and SPM levels, and their relationship with meteorological parameters such as wind velocity and relative humidity. The results have shown a marked seasonal trend and spatial variability in RSPM and SPM levels in the study area. Higher concentrations of ambient RSPM and SPM were found in downwind monitoring stations compared to upwind direction. Ratios of RSPM to SPM and correlation coefficient values between RSPM and SPM along with meteorological parameters were also worked out. Relative humidity and wind velocity have shown an inverse relation with particulate deposition pattern.     

Comparative on Causes and Accumulation of Selenium in the Tree-rings Ambient High-selenium Coal Combustion Area from Yutangba, Hubei, China

Toxic trace elements emitted during coal combustion are the main sources of air pollution. They are released into the atmosphere mainly in the forms of fine ash, smoke and flue, and thus adversely affect plant, animal and human health. Selenium is one of toxic and the most volatile in coal. Large amount of atmospheric emission of selenium, as well as selenium present and scrubber stockpiles in ash may create serious environmental problems. In the paper, on the basis of investigating the abundance and distribution of selenium in plant-rings during recent 20 years, the bioaccumulation of selenium is explained that selenium in plant, which were collected from the village of selenium-rich coal combustion, is much higher than that in plants collected away from the village of selenium-rich coal combustion. The main origins of selenium are selenium-rich coal combustion and high-selenium rock weathered. The selenium recycle by food chain and selenium will accumulate and redistribute in environments.     

南京青奥会空气质量保障工作的回顾与启示

分析了青奥会期间南京及周边城市空气质量状况;总结了保障青奥会空气质量的管控措施以及得到的启示。提出,青奥会保障机制应常态化,切实加快工业结构调整,全面控制燃煤污染,深入推进重点领域污染治理,夯实工作基础和能力。     

Evaluation of airborne lead levels in storage battery workshops and some welding environments in Kumasi metropolis in Ghana

Airborne lead levels were assessed in nine workshops, three each from battery, electronic repair, and welding sources within the Kumasi Metropolis in Ghana. Samples were collected at 0, 2.5, and 5.0 m away from the emission source at the workshops during working hours and another at 5.0 m during break hours. Airborne lead particulates were collected and analyzed using the filter membrane technique and flame atomic absorption spectrophotometry, respectively. There were significant differences (p ≤ 0.05) among the air lead levels from the workshops. Workshop 3b produced the highest significant values of air lead concentrations of 2,820.31 ± 53.89, 2,406.74 ± 71.87, 754.55 ± 72.52, and 549.01 ± 67.30 μg/m³ at distances of 0, 2.5, 5.0, and 5.0 m (break-time measurement), respectively, while workshop 1w significantly produced the lowest air lead concentration values of 261.06 ± 21.60, 190.92 ± 36.90, 86.43 ± 16.26, and 61.05 ± 3.88 μg/m³ at distances of 0, 2.5, 5.0, and 5.0 m (break-time measurement), respectively. The air lead levels reduced with distance from emission source at the workshops. At all the distances of measurement at working hours, the airborne lead levels were higher than the World Health Organization standard of 50 μg/m³ and exceeded the threshold limit values of 100 to 150 μg/m³ recommended in most jurisdictions. Workers and people in the immediate environs were exposed to air lead levels that were too high by most international standards, thus posing a serious threat to their health.     

Environmental quality assessment studies of coal handling on peripheral land near Kanika siding, Basundhra-Garjanbahal area of MCL, Sundergarh, Orissa, India

Coal has been recognized as the most important source of energy generation in India. The present work was undertaken in order to assess the environmental impact of coal handling on peripheral land under near Kanika siding, Orissa, India. The data on suspended particulates in ambient air indicates an additional load of 50.5–108.7 μg/m³) to the ambient air due to coal loading which is equivalent to 50 × 365 to 108 × 365 kg/year. However, in the southern side (opposite to siding) covering the crop fields, the dust accumulation was maximum, i.e., 0.021 to 0.035 mg/cm² area in comparison to 0.001 to 0.021 in the eastern side and 0.001 to 0.029 in western side of the crop fields. The physical and chemical properties of soil was also assessed. The results reveal that the coal loading has definite negative impact on the peripheral land near the site.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Indirect prediction of surface ozone concentration by plant growth responses in East Asia using mini-open top chambers

We developed small and mobile open top chambers (mini-OTC) measuring 0.6 m (W)?×?0.6 m (D)?×?1.2 m (H) with an air duct of 0.6 m (W)?×?0.23 m (D)?×?1.2 m (H). The air duct can be filled with activated charcoal to blow charcoal filtered air (CF) into the chamber, as opposed to non-filtered ambient air (NF). Ozone sensitive radish Raphanus sativus cv. Red Chime and rosette pakchoi Brassica campestris var. rosularis cv. ATU171 were exposed to NF and CF in mini-OTCs at different locations in East Asia. A total of 29 exposure experiments were conducted at nine locations, Shanghai, China, Ha Noi, Vietnam, Lampang, Phitsanulok and Pathumtani, Thailand, and Hiratsuka, Kisai, Abiko and Akagi, Japan. Although no significant relationships between the mean concentrations of ambient O₃ during the experimental period and the growth responses were observed for either species, multiple linear regression analysis suggested a good relationship between the biomass responses in each species and the O₃ concentration, temperature, and relative humidity. The cumulative daily mean O₃ (ppb/day) could be indirectly predicted by NF/CF based on the dry weight ratio of biomass, mean air temperature, and relative air humidity.     

Spatial and temporal distribution of polycyclic aromatic hydrocarbons (PAHs) in sediments of the Nansi Lake, China

Polycyclic aromatic hydrocarbons (PAHs) were measured in surface sediments and dated core sediments from the Nansi Lake of China to investigate the spatial and temporal distribution characteristics. The concentrations of 16 kinds priority PAH compounds were determined by GC-MS method. And ²¹⁰Pb isotope dating method was used to determine the chronological age of the sediment as well as the deposition rate. The results indicated that the total PAHs concentration ranges in surface and core sediment samples were 160 ~32,600 and 137 ~ 693 ng/g (dry wt.), respectively. The sediment rate and the average mass sedimentation were calculated to be 0.330 cm·year^???1 and 0.237 g·cm^???2·yr^???1 and the sediment time of the collected core sample ranged from 1899 to 2000. The peak of PAH concentrations came at recent years. The source analysis showed PAHs mainly came from the contamination of low temperature pyrogenic processes, such as coal combustion. The PAHs concentrations were lower than ERL and LEL values for most collected samples. However, in several surface sediment samples especially in estuary sites, the PAHs concentrations were not only higher than ERL and LEL values, but also higher than ERM values.     

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.     

Density assessment and mapping of microorganisms around a biocomposting plant in Sanandaj,Iran

Exposure to microorganisms can cause various diseases or exacerbate the excitatory responses, inflammation, dry cough and shortness of breath, reduced lung function, chronic obstructive pulmonary disease, and allergic response or allergic immune. The aim of the present study was to investigate the density of microorganisms around the air of processing facilities of a biocomposting plant. Each experiment was carried out according to ASTM E884-82 (2001) method. The samples were collected from inhaled air in four locations of the plant, which had a high traffic of workers and employees, including screen, conveyor belt, aerated compost pile, and static compost pile. The sampling was repeated five times for each location selected. The wind speed and its direction were measured using an anemometer. Temperature and humidity were also recorded at the time of sampling. The multistage impactor used for sampling was equipped with a solidified medium (agar) and a pump (with a flow rate of 28.3 l/m) for passing air through the media. It was found that the mean density of total bacteria was >1.7 × 10³ cfu/m³ in the study area. Moreover, the mean densities of fungi, intestinal bacteria (Klebsiella), and Staphylococcus aureus were 5.9 × 10³, 3.3 × 10³, and 4.1 × 10³ cfu/m³, respectively. In conclusion, according to the findings, the density of bacteria and fungi per cubic meter of air in the samples collected around the processing facilities of the biocomposting plant in Sanandaj City was higher than the microbial standard for inhaled air.     

Greenhouse gas emissions from Australian open-cut coal mines: contribution from spontaneous combustion and low-temperature oxidation

Spontaneous combustion and low-temperature oxidation of waste coal and other carbonaceous material at open-cut coal mines are potentially significant sources of greenhouse gas emissions. However, the magnitude of these emissions is largely unknown. In this study, emissions from spontaneous combustion and low-temperature oxidation were estimated for six Australian open-cut coal mines with annual coal production ranging from 1.7 to more than 16 Mt. Greenhouse emissions from all other sources at these mines were also estimated and compared to those from spontaneous combustion and low-temperature oxidation. In all cases, fugitive emission of methane was the largest source of greenhouse gas; however, in some mines, spontaneous combustion accounted for almost a third of all emissions. For one mine, it was estimated that emissions from spontaneous combustion were around 250,000 t CO₂-e per annum. The contribution from low-temperature oxidation was generally less than about 1% of the total for all six mines. Estimating areas of spoil affected by spontaneous combustion by ground-based surveys was prone to under-report the area. Airborne infrared imaging appears to be a more reliable method.