Haze Research in Brunei Darussalam During the 1998 Episode

— Brunei Darussalam experienced a severe haze episode between the beginning of February and the end of April 1998 due mainly to local peat and forest fires in Brunei and in neighbouring Sabah and Sarawak. The extensive research studies of the haze carried out in Brunei are outlined together with selected results. Particulate matter (PM₁₀) was the only significant criteria pollutant and it exceeded WHO guidelines and accepted air quality standards on most days during the haze episode. Gaseous criteria pollutants (CO, SO₂, NO₂, O₃) were generally well below WHO guidelines and at these concentrations they are expected to have no significant health or environmental effects. Measurements of volatile organic compounds (VOCs) revealed the presence of benzene, toluene, ethylbenzene, and xylenes (BTEX), aldehydes, phenol, and polynuclear aromatic hydrocarbons (PAHs). Personal exposure monitoring of PM₁₀ revealed significant differences in exposure patterns between different individuals depending on the location, time and activity. Data on outpatient visits showed an increase for some illnesses (e.g., acute respiratory infection) during the months of haze. No significant impacts of haze on rainwater acidity or deposition were noted. Emission factors for some volatile compounds were determined in combustion experiments in which peat was burned at temperatures typical of smouldering.     

Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China

In January 2013,a long-lasting episode of severe haze occurred in central and eastern China,and it attracted attention from all sectors of society.The process and evolution of haze pollution episodes were observed by the"Forming Mechanism and Control Strategies of Haze in China"group using an intensive aerosol and trace gases campaign that simultaneously obtained data at 11 ground-based observing sites in the CARE-China network.The characteristics and formation mechanism of haze pollution episodes were discussed.Five haze pollution episodes were identified in the Beijing-Tianjin-Hebei(Jing-Jin-Ji)area;the two most severe episodes occurred during 9–15 January and 25–31 January.During these two haze pollution episodes,the maximum hourly PM2.5mass concentrations in Beijing were 680 and 530μg m 3,respectively.The process and evolution of haze pollution episodes in other major cities in the Jing-Jin-Ji area,such as Shijiazhuang and Tianjin were almost the same as those observed in Beijing.The external cause of the severe haze episodes was the unusual atmospheric circulation,the depression of strong cold air activities and the very unfavorable dispersion due to geographical and meteorological conditions.However,the internal cause was the quick secondary transformation of primary gaseous pollutants to secondary aerosols,which contributed to the"explosive growth"and"sustained growth"of PM2.5.Particularly,the abnormally high amount of nitric oxide(NOx)in the haze episodes,produced by fossil fuel combustion and vehicle emissions,played a direct or indirect role in the quick secondary transformation of coal-burning sulphur dioxide(SO2)to sulphate aerosols.Furthermore,gaseous pollutants were transformed into secondary aerosols through heterogeneous reactions on the surface of fine particles,which can change the particle’s size and chemical composition.Consequently,the proportion of secondary inorganic ions,such as sulphate and nitrate,gradually increased,which enhances particle hygroscopicity and thereby accelerating formation of the haze pollution.     

Investigating Correlations and Variations of Air Pollutant Concentrations under Conditions of Rapid Industrialization – Kocaeli (1987–2009)

In this study, it was aimed to characterize temporal variations of air pollutants for determining contribution to pollution episodes and to obtain correlations between these pollutants. With this aim we used data analysis for measured sulfur dioxide (SO₂), particulate matter (PM, black fume and PM10), nitrogen oxides (NO_x), ozone (O₃), carbon monoxide (CO), methane (CH₄), and non‐methane hydrocarbons (NMHC) recorded in Kocaeli, one of the most industrilizated cities of Turkey. Pollutant concentrations were the results of continuous and semi‐automatic measurements. Semi‐automatic measurements of SO₂ and PM (black fume) were enclosing period from 1987 to 2008 whereas continuous monitoring of all pollutants included years of 2007–2009. In the first stage of the study daily, monthly, annual, and seasonal variations of pollution were researched. Annual average concentrations were compared with limits set by Air Quality Protection Regulation (AQPR), Air Quality Evaluation and Management Regulation (AQEMR), World Health Organization (WHO), European Union (EU), and National Ambient Air Quality Standards (USEPA). In the following stage relationships between pollutants such as NO₂–O₃, NO_x–CO, NO_x–NMHC, and NO_x–SO₂ were investigated and correlation coefficients were determined as 0.87, 0.56, 0.51, and 0.69, respectively. R² values of regression models developed from these correlations were 0.78, 0.56, 0.34, and 0.72, respectively. Vehicle density of the traffic was evaluated with NO_x–O₃ emissions and decrease was seen in NO_x emissions due to decreasing vehicle density at weekends whereas O₃ concentrations increased. These correlations enable prediction of the parameters that cannot be measured which is important for providing improvement in early warning systems.     

Visibility and Incidence of Respiratory Diseases During the 1998 Haze Episode in Brunei Darussalam

— Air pollution episodes as a result of forest fires in Brunei Darussalam and neighbouring regions have reached hazardous levels in recent years. Such episodes are generally associated with poor visibility and air quality conditions. In the present study, data on PM₁₀ (particulate matter of size less than 10 microns) and CO in Brunei Darussalam have been considered to study the incidence of respiratory diseases whereas data on relative humidity (RH) in addition to PM₁₀ have been used to explain the visibility with a particular emphasis on haze episode during 1998.¶Initial exploratory analysis indicates significant correlation of visibility with PM₁₀ and RH. An attempt has been made to explain visibility on the basis of PM₁₀ and RH using multiple linear regression analysis. The regression model shows that PM₁₀ and RH are two significant factors affecting the visibility at a given site. Further, canonical correlation, a multivariate method of analysis, has been used to explain the incidence of respiratory diseases as a function of air quality during the haze period. The results indicate that PM₁₀ and CO levels during the haze period have a significant bearing on the incidence of respiratory diseases (Asthma, Acute Respiratory Infections and Influenza (ARII)).     

Spatial Distribution of SO2, NO2, and O3 Concentrations in an Industrial City of Turkey Using a Passive Sampling Method

Ambient concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) were measured at 51 sampling points by passive sampling technique in Kocaeli, an important industrial city in Turkey. Samples were analyzed by UV‐spectrophotometry for NO₂ and O₃ and by ion chromatography for SO₂, respectively. Concentrations of SO₂, NO₂, and O₃ were determined to investigate their spatial distribution and source characterization. The sampling campaigns revealed an average concentration of 8 µg/m³ (max. 82 µg/m³) for SO₂, and 14 µg/m³ (max. 40 µg/m³) for NO₂, in summer; while average winter concentrations were 25 µg/m³ (max. 61 µg/m³) for SO₂, and 50 µg/m³ (max. 100 µg/m³) for NO₂. The maximum ozone concentrations were determined to be 86 µg/m³ in summer and 61 µg/m³ in winter downwind of the source areas of the precursor pollutant emissions. The results showed that NO₂ and SO₂ concentrations in industrial and urban areas were two to four times higher compared with rural areas in the summer and winter. In the light of the information obtained from the spatial interpolation of the pollutant concentrations, a selection of appropriate locations for continuous monitoring was suggested according to the European Community (EU) directives.     

Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai,China

The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO₂ (from 2 to 14%) and for PM₁₀ (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO₂ in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO₂ and 19% for NO₂ decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future.     

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi-Natural Experiment

In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM₁₀ (27%), PM_2.5 (19%), NO₂ (74%), SO₂ (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m⁻³ in PM₁₀, 23 µg m⁻³ in PM_2.5, 14 µg m⁻³ in NO₂, 2 µg m⁻³ in SO₂, and 0.7 mg m⁻³ in CO can be achieved.     

Finding regions of influence on SO2 and SO= 4 daily concentration measurements at four sites in Spain

Contamination by the pollutants SO₂ and SO⁼₄ was analyzed for the 1989–1992 period at four regional stations in Spain under the auspices of the EMEP-BAPMON program. The evolution of the time series of the daily pollution has also been assessed, and high mean concentrations at La Cartuja and Logroño observed, with values of 3.8 and 4.5 g m⁻³ for SO₂, respectively. Maximum annual concentrations were recorded in 1989, when SO₂ reached values of 6.24, 5.39, 5.71, and 9.30 g m⁻³ for the stations of La Cartuja, San Pablo de los Montes, Roquetas, and Logroño, respectively. This work attempts to establish a relationship between the concentrations of the pollutants - both SO₂ gas and SO⁼₄ aerosol - and the zones of emission or persistence of these long-range transported pollutants. In this way, those regions showing a greater impact on the air quality in each season have been determined. To achieve this, the trajectories of the air masses carrying away the pollution to each of the receiving stations were considered and followed by a sectorial analysis. Nonparametric statistical methods were implemented to contrast the chemical homogeneity among the different sectors. The criterion that several homogeneous sectors form a chemically homogeneous region was used. To improve this sectorial analysis, we have proposed a new technique based on the Potential-Source-Contribution Function (PSCF). Starting out from a set of specified regions, considered to be chemically homogeneous domains, it is possible to determine the likelihood that an air mass with particular characteristics (e.g., that a value of the daily concentration higher than the mean recorded at the station has been obtained) will arrive at a given station after having crossed one of the previously defined regions. Using this technique, it is possible to determine the source regions through which the air masses circulate and bring high pollution concentrations to the studied stations. Thanks to the PSCF, these statistical methods offer, through a sectorial analysis, the possibility to pass from a qualitative to a more quantitative view.     

Pollutant Concentrations in Mountain River Waters in the Upper Baksan Area (Prielbrus’e National Park) and Their Seasonal Variations

Materials of expedition studies in 2013 in the Prielbrus’e National Park were used to analyze the concentrations of a wide range of pollutants (SO₄^2-, Cl^?, Na⁺, K⁺, F^?, Mn, Cu, Zn, Pb, Cr, Ni, NO₃^-, NH₄⁺) in the water of mountain rivers forming the main artery of the region, the Baksan R. The analyzed data characterize seasonal variations in pollutant concentrations at seven sampling sections and their dynamics along the river down to the 35th km from the source in different seasons.     

Chemostatic behaviour of major ions and contaminants in a semiarid spring and stream system near Los Alamos,NM, USA

Recent studies have focused on the relationship between solute concentrations and discharge in streams, demonstrating that concentrations can vary little relative to changes in discharge (chemostatic behaviour). Chemostatic behaviour is dependent on catchment characteristics (e.g., lithology, geomorphology, and vegetation) and chemical characteristics of the solute (e.g., availability, reactivity, and mobility). An investigation of 3 springs and a stream near Los Alamos, NM, reveals that springs can behave in a chemostatic fashion as stream systems tend to do. Another unique finding of this study is that the anthropogenic contaminants barium and the high explosive RDX (hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine) can also behave chemostatically. The chemostatic behaviour of a contaminant has important implications for the residence time of contaminants in a system as well as having a major control on contaminant flux and mass transport. Redox (reduction–oxidation) and biogeochemically sensitive analytes (e.g., Fe, SO₄, and NO₃) display a combination of chemostatic and chemodynamic behaviour, showing the influence of temporally variable conditions on stream and spring chemistries.     

Hydrology and nutrient dynamics of spring of almora-binsar area, indian central himalaya: Landscapes, practices, and management

The study aims to measure the hydrological behavior and nutrients dynamics of the springs located in different landscapes of Kosi basin, Indian central Himalaya. A total number of eight springs were considered for the present investigation, each landscape represented by one spring. The monitoring for hydrological measurement was conducted in January 1998 to December 1999, the interval between two successive measurements was 10 days, i.e., 240 hr (total 72 observations were made). Water quality measurement was done in three main seasons, i.e., winter (Jan.), summer (June) and monsoon (Aug.) of 1998 and 1999, and the average value for measured parameters were calculated. These samples were analyzed for pH, electrical conductivity, total dissolved solids, dissolve oxygen, Ca^2?, Mg^2?, Na^?, Cl^?, F^?, NO ₃ ^? , and SO ₄ ^2? . Hydrology of spring’s water showed that the reserve forest has a higher water retention capacity than the other landscapes, and the spring recharge capacity highly influenced by the settlements, open grazing, mismanaged agricultural and deforestation activities. The spring water chemistry shows that the springs located in forest and sparsely populated areas have lower EC, TDS, cationic and anionic concentration and are safe for drinking purposes, but those in irrigated land and densely populated areas feature higher EC, low dissolved oxygen concentration and higher NO ₃ ^? , which makes the water of these springs unsuitable for drinking. F concentration was higher in the springs located in the settlement area. In brief, the study indicates that the unmanaged drains, very poor and old pattern of sewage disposing system result in an increase in Na^?, Cl^?, F^?, NO ₃ ^? , and SO ₄ ^2? concentration as compared to the springs in agricultural and forested areas. All of the studied springs are badly managed which a is great threat for the longevity and quality of the water bodies, in particular, in Indian Central Himalayan region. This study suggests the ways of the constructional works, grazing. Forest resource extraction and agricultural activities in water bodies catchments area should also be controlled.     

Hydrochemical characteristics of throughfall and stemflow in a Moso‐bamboo (Phyllostachys pubescens) forest

To investigate the impacts of the invasion by bamboo on fluxes of nutrients and pollutants, the nutrient/pollutant fluxes and canopy interactions, including neutralization of acidity, leaching and uptake of nitrogen (N), were characterized in conjunction with rainfall partitioning in a Moso‐bamboo (Phyllostachys pubescens) forest. Measurements of precipitation volume, pH, major ions, and silicate (SiO₂) in rainfall, throughfall and stemflow were collected weekly in a Moso‐bamboo forest located in Munakata City, Western Japan for 1 year. Results showed that rainfall partitioning into stemflow was larger than that for other types of forest, which may be due to the properties of Moso‐bamboo forest structure, such as a straight and smooth culm. Inorganic N (NO₃⁻ + NH₄⁺) and S (SO₄²⁻) fluxes of throughfall and stemflow were approximately 1·6 and 1·3 times higher than that of rainfall, respectively. Contribution of stemflow flux to inorganic N and S fluxes to the forest floor was high. This could be due to lower uptake of inorganic N through culm and a higher rainfall partitioning into stemflow than that for other types of forest. The Moso‐bamboo canopy neutralized rainfall acidity, reducing the fluxes of potentially acidifying compounds via throughfall and stemflow. Canopy leaching of K⁺ was distinctly higher than that of Mg²⁺ and Ca²⁺ and could be related to the high mobility of K⁺ in plant tissues. Cl⁻ and SiO₂ were readily leached as for K⁺. The impact of the invasion by bamboo on nutrient cycling was discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimation of PM<Subscript>10</Subscript> concentration from air quality data in the vicinity of a major steelworks site in the metropolitan area of Avilés (Northern Spain) using machine learning techniques

Atmospheric particulate matter (PM) is one of the pollutants that may have a significant impact on human health. Data collected over 7 years from the air quality monitoring station at the LD-III steelworks, belonging to the Arcelor-Mittal Steel Company, located in the metropolitan area of Avilés (Principality of Asturias, Northern Spain), is analyzed using four different mathematical models: vector autoregressive moving-average, autoregressive integrated moving-average (ARIMA), multilayer perceptron neural networks and support vector machines with regression. Measured monthly, the average concentration of pollutants (SO₂, NO and NO₂) and PM₁₀ (particles with a diameter less than ?10 μm) is used as input to forecast the monthly average concentration of PM₁₀ from one to 7 months ahead. Simulations showed that the ARIMA model performs better than the other models when forecasting 1 month ahead, while in the forecast from one to 9 months ahead the best performance is given by the support vector regression.     

Changes in groundwater bacterial community during cyclic groundwater-table variations

Column experiments containing an aquifer sand were subjected to static and oscillating water tables to investigate the impact of natural fluctuations and rainfall infiltration on the groundwater bacterial community just below the phreatic surface, and its association with the geochemistry. Once the columns were established, the continuously saturated zone was anoxic in all three columns. The rate of soil organic matter (SOM) mineralization was higher when the water table varied cyclically than when it was static due to the greater availability of NO₃⁻ and SO₄²⁻. Natural fluctuations in the water table resulted in a similar NO₃⁻ concentration to that observed with a static water table but the cyclic wetting of the intermittently saturated zone resulted in a higher SO₄²⁻ concentration. Rainfall infiltration induced cyclic water-table variations resulted in a higher NO₃⁻ concentration than those in the other two columns, and a SO₄²⁻ concentration intermediate between those columns. As rainwater infiltration resulted in slow downward displacement of the groundwater, it is inferred that NO₃⁻ and SO₄²⁻ were being mobilized from the vadose zone. NO₃⁻ was mainly released by SOM mineralization (which was enhanced by the infiltration of oxygenated rainwater), but the larger amount of SO₄²⁻ release required a second mechanism (possibly desorption). Different groundwater bacterial communities evolved from initially similar populations due to the different groundwater histories.     

The GEOMON network of Czech catchments provides long-term insights into altered forest biogeochemistry: From acid atmospheric deposition to climate change

In 1994, a network of small catchments (GEOMON) was established in the Czech Republic to determine input–output element fluxes in semi-natural forest ecosystems recovering from anthropogenic acidification. The network consists from 16 catchments and the primary observations of elements fluxes were complemented by monitoring of biomass stock, element pools in soil and vegetation, and the main water balance components. Over last three decades, reductions of SO₂, NO_x and NH₃ emissions were followed by sulphur (S) and nitrogen (N) deposition reductions of 75% and 30%, respectively. Steeper declines of strong acid anion concentrations compared to cations (Ca, Mg, Na, K, NH₄) in precipitation resulted in precipitation pH increase from 4.5 to 5.2 in bulk precipitation and from 4.0 to 5.1 in spruce throughfall. Stream chemistry responded to changes in deposition: S leaching declined. However at majority of catchments soils acted as a net source of S to runoff, delaying recovery. Stream pH increased at acidic streams (pH < 6) and aluminium concentration decreased. Stream nitrate (NO₃) concentration declined by 60%, considerably more than N deposition. Stream NO₃ concentration was tightly positively related to stream total dissolved nitrogen to total phosphorus (P) ratio, suggesting the role of P availability on N retention. Trends in dissolved organic carbon fluxes responded to both acidification recovery and to runoff temporal variation. An exceptional drought occurred between 2014 and 2019. Over this recent period, streamflow decreased by ≈ 40% on average compared to 1990s, due to the increases of soil evaporation and vegetation transpiration by ≈ 30% and declines in precipitation by ≈ 15% on average across the elevational gradient. Sharp decreases of stream runoff at catchments <650 m a.s.l. corresponded to areas of recent forest decline caused by bark beetle infestation on drought stressed spruce forests. Understanding of the interactions among legacies of acidification and eutrophication, drought effects on the water cycle and forest disturbance dynamics is requisite for effective management of forested ecosystems under anthropogenic influence.     

ARIMA forecasting of ambient air pollutants (O3, NO, NO2 and CO)

In the present study, a stationary stochastic ARMA/ARIMA [Autoregressive Moving (Integrated) Average] modelling approach has been adapted to forecast daily mean ambient air pollutants (O₃, CO, NO and NO₂) concentration at an urban traffic site (ITO) of Delhi, India. Suitable variance stabilizing transformation has been applied to each time series in order to make them covariance stationary in a consistent way. A combination of different information-criterions, namely, AIC (Akaike Information Criterion), HIC (Hannon–Quinn Information Criterion), BIC (Bayesian Information criterion), and FPE (Final Prediction Error) in addition to ACF (autocorrelation function) and PACF (partial autocorrelation function) inspection, has been tried out to obtain suitable orders of autoregressive (p) and moving average (q) parameters for the ARMA(p,q)/ARIMA(p,d,q) models. Forecasting performance of the selected ARMA(p,q)/ARIMA(p,d,q) models has been evaluated on the basis of MAPE (mean absolute percentage error), MAE (mean absolute error) and RMSE (root mean square error) indicators. For 20 out of sample forecasts, one step (i.e., one day) ahead MAPE for CO, NO₂, NO and O₃, have been found to be 13.6, 12.1, 21.8 and 24.1%, respectively. Given the stochastic nature of air pollutants data and in the light of earlier reported studies regarding air pollutants forecasts, the forecasting performance of the present approach is satisfactory and the suggested forecasting procedure can be effectively utilized for short term air quality forewarning purposes.     

三峡大坝上下游水质时空变化特征

为探索三峡大坝上下游（坝上99.9 km、坝下63.0 km、全长162.9 km）水质时空变化特征,运用主成分分析和方差分析对2016年近坝段水质时空变化特征进行了分析.主成分分析表明,水文因子流量（Q）、气温（T）、水位（Z）和水质因子（水温（WT）、pH、电导率（EC）、溶解氧（DO）、悬浮物（SS）、高锰酸盐指数（COD_Mn）、硫酸盐（SO₄^2-）、氟化物（F^-）、总硬度（T-Hard）、硝态氮（NO₃^--N）、总氮（TN）和硒（Se））的变化主导着研究区域水质变化;各采样点主成分得分和双因素方差分析结果显示研究区域水质因子时间变化主要呈现出季节和不同水库运行时期的差异.消落期（2-5月）,T-Hard、F^-、SO₄^2-和EC是影响河流水质变化的主导因子;汛期（7-8月）,Q、SS、COD_Mn、NO₃^--N、TN和Se是影响河流水质变化的主导因子;T和WT主导着汛末（9月）河流水质变化,并引起了DO等理化特性的变化;高水位运行期（12月）,Cl^-是影响河流水质变化的主导因子.现阶段,DO、有机污染物（COD_Mn）、无机盐（SO₄^2-和F^-）、营养盐类（NO₃^--N和TN）、类金属元素（Se）和水体的矿化程度（T-Hard）的变化主导着区域水质的变化,是三峡大坝近坝段水域水质的控制因子.方差分析表明,河流的理化特性（DO、pH和SS）、营养盐组分构成（NH₃-N和NO₃^--N）、无机盐类（EC和Cl^-）、石油类有机污染物及粪大肠菌群（FC）等指标在坝上与坝下断面存在显著性差异.气温、水温、降雨、含沙量的季节性影响因素和水库调度运行模式是影响近坝段水质时间差异的主要因子;空间差异主要受城区污染排放和三峡水库调度引起的坝上和坝下水文和水动力学条件差异影响.因此控制研究区域因人类活动等造成的外源性污染,并针对不同类污染物质的季节变化特征实施合理的水库运行方式是近坝段水质提升的关键.     

IDOAS: A new monitoring technique to study the 2D distribution of volcanic gas emissions

Imaging Differential Optical Absorption Spectroscopy (IDOAS) is an optical remote-sensing method using scattered sunlight as light source. It combines a “pushbroom” imaging spectrometer with the DOAS technique and thus allows imaging two-dimensional trace gas distributions, e.g., in volcanic plumes. The highly sensitive and specific detection of many trace gases simultaneously (specific molecules, not just elements, e.g. SO₂, BrO, NO₂, O₃, HCHO, etc.) is possible, and the temporal and spatial variation of these gases can be measured. The IDOAS system presented here enables the taking of two-dimensional images of trace gas distributions in a volcanic plume with a spatial resolution of 100 pixels horizontally × 64 pixels vertically, each with a field of view of 0.087° in horizontal and 0.208° in vertical directions. Therefore, IDOAS provides useful information about the chemical composition and chemical variability in a volcanic plume and allows studying plume dispersal and chemical transformations. The technique was applied to map the SO₂ distribution in the plume of Mt. Etna volcano for the first time in October 2003.     

Effect of intensity and duration of freezing on soil microbial biomass,extractable C and N pools,and N2O and CO2 emissions from forest soils in cold temperate region

Freezing can increase the emissions of carbon dioxide(CO_2) and nitrous oxide(N_2O) and the release of labile carbon(C) and nitrogen(N) pools into the soil. However, there is limited knowledge about how both emissions respond differently to soil freezing and their relationships to soil properties. We evaluated the effect of intensity and duration of freezing on the emissions of CO_2 and N_2 O, net N mineralization, microbial biomass, and extractable C and N pools in soils from a mature broadleaf and Korean pine mixed forest and an adjacent secondary white birch forest in northeastern China. These soils had different contents of microbial biomass and bulk density. Intact soil cores of 0–5 cm and 5–10 cm depth sampled from the two temperate forest floors were subjected to -8, -18, and -80°C freezing treatments for a short(10 d) and long(145 d) duration, and then respectively incubated at 10°C for 21 d. Soil cores, incubated at 10°C for 21 d without a pretreatment of freezing, served as control. Emissions of N_2 O and CO_2 after thaw varied with forest type, soil depth, and freezing treatment. The difference could be induced by the soil water-filled pore space(WFPS) during incubation and availability of substrates for N_2 O and CO_2 production, which are released by freezing. A maximum N_2 O emission following thawing of frozen soils was observed at approximately 80% WFPS, whereas CO_2 emission from soils after thaw significantly increased with increasing WFPS. The soil dissolved organic C just after freezing treatment and CO_2 emission increased with increase of freezing duration, which paralleled with a decrease in soil microbial biomass C. The cumulative net N mineralization and net ammonification after freezing treatment as well as N_2 O emission were significantly affected by freezing temperature. The N_2 O emission was negatively correlated to soil p H and bulk density, but positively correlated to soil K_2SO_4-extractable NO_3~--N content and net ammonification. The CO_2 emission was positively correlated to the cumulative net N mineralization and net ammonification. From the above results, it can be reasonably concluded that for a wide range of freezing temperature and freezing duration, N_2 O and CO_2 emissions after thaw were associated mainly with the changes in soil net N mineralization and the availability of substrate liberated by freezing as well as other soil properties that influence porosity.     

Variations in trace gas concentrations in different environments in India

Observations of trace gases (SO₂, NH₃, NO₂ and O₃) were made during the period 1981 to 1984 at 6 different locations representative of urban industrial, urban, nonurban, thermal power plant and marine environment. Diurnal variations of the trace gases were studied in an urban environment. Except in the urban industrial environment, the concentration of NH₃ was found in the range of background values. Also, the average concentrations of NO₂ and O₃ at the different environments were in the order of background values. However, the concentrations of SO₂ were substantially higher by about 7 times, in urban industrial and thermal power plant environments. The diurnal variations of SO₂, NH₃ and NO₂ showed anitphase relationship with surface temperature at the urban environment station which is relatively free of industrial pollution. Discussion is centred on trace gas variations in different environments in India together with the values reported for various countries in the world.