Transport of NO<Subscript>X</Subscript> Emissions from Sugarcane Fertilisation into the Great Barrier Reef Lagoon

The Great Barrier Reef World Heritage Area contains highly sensitive ecosystems that are threatened by the effects of anthropogenic activity including eutrophication. The nearby sugarcane plantations of tropical north Queensland are fertilised annually and there has been ongoing concern about the magnitude of the loss of applied nitrogen to the environment. Previous studies have considered the potential of rainwater run-off to deposit reactive nitrogen species into rivers and ultimately into the Great Barrier Reef Lagoon, but have neglected the possibility of transport via the atmosphere. This paper reports the results of a modelling study commissioned by Australia’s National Heritage Trust aimed at assessing whether or not atmospheric deposition of reactive nitrogen from Queensland’s sugarcane plantations posed a potential threat to the Great Barrier Reef Lagoon. Atmospheric dispersion modelling was undertaken using The Air Pollution Model, developed by Australia’s Commonwealth Scientific and Industrial Research Organisation. Despite the predominance of onshore southeasterly winds, the dispersion model results indicate that 9% of the time during the sugarcane fertilization season (in the modeled years 2001–2006) the meteorological conditions resulted in emissions from the coastal regions of north Queensland being transported out over the ocean around the Great Barrier Reef. The results suggest that there may be a greater efficiency for transport out over the reef during October than for November and December. For the 2 months that exhibited the greatest potential for transport of coastal pollution to the Great Barrier Reef, the modeled deposition of nitrogen oxides (NO_X) into the Great Barrier Reef lagoon was less than 1% of the total emissions from the sugarcane plantations, but was not zero. Our model has a simple chemical scheme that does not cover the full chemistry of all reactive nitrogen compounds and so the results are only indicative of the potential levels of deposition. Nevertheless, our study shows that small amounts of NO_X that originate from sugarcane fertilization may be transported and dry deposited into the Great Barrier Reef lagoon. Other pathways not included in the modeling scheme may provide a more efficient transport mechanism. Whilst modern practices for the application of fertilizer to sugarcane plantations have drastically reduced emissions, the potential efficiency of transport of pollutants via the atmosphere may be of concern for other more highly polluting agricultural industries.     

Simultaneous measurements of dissolved CH<Subscript>4</Subscript> and H<Subscript>2</Subscript> in wetland soils

Biogeochemical processes in wetland soils are complex and are driven by a microbiological community that competes for resources and affects the soil chemistry. Depending on the availability of various electron acceptors, the high carbon input to wetland soils can make them important sources of methane production and emissions. There are two significant pathways for methanogenesis: acetoclastic and hydrogenotrophic methanogenesis. The hydrogenotrophic pathway is dependent on the availability of dissolved hydrogen gas (H₂), and there is significant competition for available H₂. This study presents simultaneous measurements of dissolved methane and H₂ over a 2-year period at three tidal marshes in the New Jersey Meadowlands. Methane reservoirs show a significant correlation with dissolved organic carbon, temperature, and methane emissions, whereas the H₂ concentrations measured with dialysis samplers do not show significant relationships with these field variables. Data presented in this study show that increased dissolved H₂ reservoirs in wetland soils correlate with decreased methane reservoirs, which is consistent with studies that have shown that elevated levels of H₂ inhibit methane production by inhibiting propionate fermentation, resulting in less acetate production and hence decreasing the contribution of acetoclastic methanogenesis to the overall production of methane.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

Industrial point source CO<Subscript>2</Subscript> emission strength estimation with aircraft measurements and dispersion modelling

CO₂ remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO₂ emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO₂ industrial point source, located in Biganos, France. CO₂ density measurements were obtained by applying the mass balance method, while CO₂ emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.     

Influence of burning of fireworks on particle size distribution of PM<Subscript>10</Subscript> and associated Barium at Nagpur

Influence of burning of fireworks on particle size distribution of PM₁₀ and associated barium (Ba) were studied at a congested residential cum commercial area of Nagpur city, India. Sampling was carried out by cascade impactor having 50% cut-off aerodynamic diameters of <10, 9, 5.8, 4.7, 3.3, 2.1, 1.1, 0.7, and <0.4 μm, 2 days before diwali, during diwali, celebrations of marriage functions, and New Year’s Eve. Noticeably, increased levels of PM₁₀ and Ba were observed during diwali as compared to days before diwali and other activities. PM₁₀ levels were increased by four to nine times whereas Ba levels were increased by eight to 20 times higher in alveolar region, when compared with the levels observed before diwali. Probability of deposition of Ba mass in alveolar region varied between 14 and 27 ng/h with higher deposition when the burning of fireworks activity was lower near the site. Trimodal distribution of Ba was observed on the first 2 days of diwali at 0.4–2.1, 2.1–4.7, and 4.7 to less than PM₁₀ micrometer range. While on the third day, it appeared bimodal with 70% contribution in coarse fraction whereas on the fourth day, distribution appeared unimodal with 66% contribution in alveolar region (<0.4–1.1 μm). Distribution of Ba varied with respect to particle size, in accordance with the intensity of the fireworks used on different days and distance between the burning of firecrackers from the monitoring site.     

Relationships of relative humidity with PM<Subscript>2.5</Subscript> and PM<Subscript>10</Subscript> in the Yangtze River Delta,China

Severe particulate matter (PM, including PM_2.5 and PM₁₀) pollution frequently impacts many cities in the Yangtze River Delta (YRD) in China, which has aroused growing concern. In this study, we examined the associations between relative humidity (RH) and PM pollution using the equal step-size statistical method. Our results revealed that RH had an inverted U-shaped relationship with PM_2.5 concentrations (peaking at RH = 45–70%), and an inverted V-shaped relationship (peaking at RH = 40 ± 5%) with PM₁₀, SO₂, and NO₂. The trends of polluted-day number significantly changed at RH = 70%. The very-dry (RH < 45%), dry (RH = 45–60%) and low-humidity (RH = 60–70%) conditions positively affected PM_2.5 and exerted an accumulation effect, while the mid-humidity (RH = 70–80%), high-humidity (RH = 80–90%), and extreme-humidity (RH = 90–100%) conditions played a significant role in reducing particle concentrations. For PM₁₀, the accumulation and reduction effects of RH were split at RH = 45%. Moreover, an upward slope in the PM_2.5/PM₁₀ ratio indicated that the accumulation effects from increasing RH were more intense on PM_2.5 than on PM₁₀, while the opposite was noticed for the reduction effects. Secondary transformations from SO₂ and NO₂ to sulfate and nitrate were mainly responsible for PM_2.5 pollution, and thus, controlling these precursors is effective in mitigating the PM pollution in the YRD, especially during winter. The conclusions in this study will be helpful for regional air-quality management.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

重点城市空气质量日报分析和图形表征技术研究

介绍了利用数据库管理系统和ArcGIS平台开发的全国重点城市空气质量空间查询、分析和图形表征系统,较好地利用全国重点城市空气质量日报数据分析全国空气质量时间变化趋势和空间区域分布.     

Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

Study of the PM<Subscript>10</Subscript> concentration variations along two intra-urban roads within a compact city

Eighty-five measurement campaigns were performed repeatedly to compare the concentration variation profiles along two intra-urban roads—one with open configuration and the other with street canyon effect. Fixed-effects panel data analysis was applied for formulating a model to express the PM₁₀ concentrations along intra-urban roads in terms of parameters like nearby central monitoring data, traffic counts and meteorological conditions with an objective to analyze the PM₁₀ concentration variation patterns along the two roads. Our findings reveal that traffic intensity and metrological conditions exert influence on concentration variation for both types of road configurations while wind velocity only affect the pollutants removal effectiveness of open road configuration. Further analysis unveils that the PM₁₀ concentration distribution profiles within a compact city environment are not always uniform and are dependent on the road configuration. Considerable PM₁₀ concentration differences were observed along the street canyon, and 70% of their variations are attributed to variations in their road aspect ratios. By contrast, no significant concentration difference is observed at open road configurations.     

Laboratory and field comparison of measurements obtained using the available diffusive samplers for ozone and nitrogen dioxide in ambient air

This study presents an evaluation of the extent of differences between measurements performed by O(3) and NO(2) diffusive samplers and by the reference methods for diffusive samplers commercially available. The tests were performed in an exposure chamber under extreme conditions of controlling factors and under field conditions. For NO(2), the results of the laboratory experiments showed that most of the diffusive samplers were affected by extreme exposure conditions. The agreement between the samplers and the reference method was better for the field tests than for the laboratory ones. The estimate of the uptake rate for the exposure conditions using a model equation improved the agreement between the diffusive samplers and the reference methods. The agreement between O(3) measured by the diffusive samplers and by the reference method was satisfactory for 1-week exposure. For 8-hour exposures, the diffusive samplers with high uptake rates quantified better the O(3) concentration than the samplers with low uptake rates. As for NO(2), the results of the O(3) field tests were in better agreement with the reference method than the ones of the laboratory tests. The field tests showed that the majority of diffusive samplers fulfils the 25% uncertainty requirement of the NO(2) European Directive and the 30% uncertainty requirement of the O(3) European Directive for 1-week exposure.     

河南省环境空气质量监测网优化的研究

在全省城市环境空气质量监测网优化并运行六年的基础上 ,采用历史数据计算法对河南省环境空气质量监测网进行了优化。通过优化方法和监测项目的探索 ,确定了省控站数目 ,特别是提出了系统、完整的优化指标 ,优化结果是令人满意的。     

Presence of aflatoxin M<Subscript>1</Subscript> in raw,reconstituted, and powdered milk samples collected in Algeria

Aflatoxins are potent toxic metabolites produced by Aspergillus spp. Aflatoxin M₁ (AFM1) is a metabolite of aflatoxin B₁ that can be present in milk, and it is a public health concern. There is scarce information on the incidence of aflatoxin M₁ contamination in milk consumed in Algeria. The presence of AFM1 was investigated in raw milk samples collected between February and October 2011 from 11 dairy farms representative of Algerian production conditions and that were located around Constantine city. Reconstituted and powdered milk samples were purchased from local supermarkets. The analysis was performed by liquid chromatography-fluorescence detection after immunoaffinity purification. AFM1 was detected in 5 out of 47 samples (11 %) at levels ranging from 9 to 103 ng/L, with one sample exceeding the limit of 50 ng/L set by European regulations. Traces of AFM1 (less than 8 ng/L) were also found in 11 other samples. The incidence of AFM1 contamination was higher in imported powdered milk (29 %) than in raw milk (5 %). Although the concentration of AFM1 in contaminated samples was low, the relatively considerable prevalence found in this exploratory study justifies more detailed and continuous monitoring to reduce consumers’ exposure to AFM1.     

Effect of pendimethalin and quizalofop on N<Subscript>2</Subscript>-fixing bacteria in relation to availability of nitrogen in a <Emphasis Type="Italic">Typic Haplustept</Emphasis> soil of West Bengal,India

An experiment was conducted under laboratory conditions to investigate the effect of two systemic herbicides viz., pendimethalin and quizalofop, at their recommended field rates (1.0 kg and 50 g active ingredient ha^− 1, respectively) on the growth and activities of non-symbiotic N₂-fixing bacteria in relation to mineralization and availability of nitrogen in a Typic Haplustept soil. Both the herbicides, either singly or in a combination, stimulated the growth and activities of N₂-fixing bacteria resulting in higher mineralization and availability of nitrogen in soil. The single application of quizalofop increased the proliferation of aerobic non-symbiotic N₂-fixing bacteria to the highest extent while that of pendimethalin exerted maximum stimulation to their N₂-fixing capacity in soil. Both the herbicides, either alone or in a combination, did not have any significant difference in the stimulation of total nitrogen content and availability of exchangeable NH₄ ⁺ while the solubility of NO₃ ⁻ was highly manifested when the herbicides were applied separately in soil.     

Seasonal variations and source profile of <Emphasis Type="Italic">n</Emphasis>-alkanes in particulate matter (PM<Subscript>10</Subscript>) at a heavy traffic site,Delhi

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m³) in PM₁₀ was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m³, along with the diagnostic tools has been calculated. The values of CPI₁, CPI₂, and CPI₃ for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C _max were at C₂₅ and C₂₇. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m³) than during the summer season (56.3 ± 1.1 ng/m³).     

Modeling seasonal variations of long-term soil CO<Subscript>2</Subscript> emissions in an orchard plantation in a semiarid area,SE Turkey

Emissions of soil CO₂ under different management systems have a significant effect on the carbon balance in the atmosphere. Soil CO₂ emissions were measured from an apricot orchard at two different locations: under the crown of trees (CO₂-UC) and between tree rows (CO₂-BR). For comparison, one other measurement was performed on bare soil (CO₂-BS) located next to the orchard field. Analytical data were obtained weekly during 8 years from April 2008 to December 2016. Various environmental parameters such as air temperature, soil temperature at different depths, soil moisture, rainfall, and relative humidity were used for modeling and estimating the long-term seasonal variations in soil CO₂ emissions using two different methods: generalized linear model (GLM) and artificial neural network (ANN). Before modeling, data were randomly split into two parts, one for calibration and the second for validation, with a varying number of samples in each part. Performances of the models were compared and evaluated using means absolute of estimations (MAE), square root of mean of prediction (RMSEP), and coefficient of determination (R²) values. CO₂-UC, CO₂-BR, and CO₂-BS values ranged from 11 to 3985, from 9 to 2365, and from 8 to 1722 kg ha^?1 week^?1, respectively. Soil CO₂ emissions were significantly correlated (p?<?0.05) with some environmental variables. The results showed that GLM and ANN models provided similar accuracies in modeling and estimating soil CO₂ emissions, as the number of samples in the validation data set increased. The ANN was more advantageous than GLM models by providing a better fit between actual observations and predictions and lower RMSEP and MAE values. The results suggested that the success of environmental variables for estimations of CO₂ emissions using the two methods was moderate.     

A study on the orbit of air temperature movement

In this paper, we describe an air temperature movement by mapping its time series to the polar coordinates: the value of the time series is plotted on the radial coordinate and the time on the angular coordinate. In this way, both the yearly and daily air temperature movements from five different locations of China are used to demonstrate that, in an intuitionistic view, air temperature movement is neither random nor chaotic, but has its own orbit. We then propose an elliptic orbit model for the air temperature movement. Our proposed model provides quite good results when it is applied to the evaluation of yearly air temperature movements in eight locations in various parts of the world, and the evaluation of daily air temperature movements in five locations in Hunan Province of China on December 17, 2005. Results show that our approach provides a concise and helpful model for air temperature analysis.     

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O<Subscript>3</Subscript> Air Quality Monitoring Network in Vojvodina Province,Serbia

A monitoring network of ground-level ozone (O₃) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O₃ monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O₃ monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.     

相似分析在空气连续监测缺测资料插补处理中的应用

空气连续自动监测中缺测资料的插补处理是环境监测与科研的一项基础性的技术工作,文章应用数理统计中的相似分析原理进行探讨,取得了较理想的结果.该方法对解决和处理因采样时间不足而造成的污染物浓度日均值缺失问题是十分有效的,对目前我国开展的城市空气质量日报工作有一定的实际意义.