Time series analysis and forecasting for air pollution in small urban area: an SARIMA and factor analysis approach

Despite the existing public and government measures for monitoring and control of air quality in Bulgaria, in many regions, including typical and most numerous small towns, air quality is not satisfactory. In this paper, factor analysis and Box–Jenkins methodology are applied to examine concentrations of primary air pollutants such as NO, NO₂, NO_x, PM10, SO₂ and ground level O₃ in the town of Blagoevgrad, Bulgaria within a 1 year period from 1st September 2011 to 31st August 2012, based on hourly measurements. By using factor analysis with PCA and Promax rotation, a high multicollinearity between the six pollutants has been detected. The pollutants were grouped in three factors and the degree of contribution of the factors to the overall pollution was determined. This was interpreted as the presence of common sources of pollution. The main part of the study involves the performance of time series analysis and the development of univariate stochastic seasonal autoregressive integrated moving average (ARIMA) models with recording on a hourly basis as seasonality. The study also incorporates the Yeo–Johnson power transformation for variance stabilizing of the data and model selection by using Bayersian information criterion. The obtained SARIMA models demonstrated very good fitting performance with regard to the observed air pollutants and short-term predictions for 72 h ahead, in particular in the case of ozone and particulate matter PM10. The presented statistical approaches allow the building of non-complex models, effective for short-term air pollution forecasting and useful for advance warning purposes in urban areas.     

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.     

Assessment of regional air pollution distribution by point cumulative semivariogram method at Erzurum urban center, TURKEY

In the assessment of air quality, regional distribution and dispersion with distance are important, together with the variations of pollutants in time. On this occasion, the point cumulative semi-variogram (PCSV) method is used in order to find simply regional distribution of pollutants of Erzurum urban centre. This method is based simply on the summation of square differences in air pollutant concentrations between different sites. Monthly regional variation maps of Erzurum are constructed by finding radius of influence (for SO₂, from 1000 m to 3500 m and, for TSP, 1000–2000 m) and PCSV scattering diagram data at different levels by using monthly average sulphur dioxide (SO₂) and total suspended particulate (TSP) matter concentrations in 2001–2002 winter season. Consequently, the air pollution distribution of Erzurum is assessed.     

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.     

Atmospheric Concentrations and Phase Partitioning of Polycyclic Aromatic Hydrocarbons in Izmir,Turkey

Ambient air polycyclic aromatic hydrocarbon (PAH) samples were collected at a suburban (n = 63) and at an urban site (n = 14) in Izmir, Turkey. Average gas‐phase total PAH (∑₁₄PAH) concentrations were 23.5 ng m^?3 for suburban and 109.7 ng m^?3 for urban sites while average particle‐phase total PAH concentrations were 12.3 and 34.5 ng m^?3 for suburban and urban sites, respectively. Higher ambient PAH concentrations were measured in the gas‐phase and ∑₁₄PAH concentrations were dominated by lower molecular weight PAHs. Multiple linear regression analysis indicated that the meteorological parameters were effective on ambient PAH concentrations. Emission sources of particle‐phase PAHs were investigated using a diagnostic plot of fluorene (FLN)/(fluorine + pyrene; PY) versus indeno[1,2,3‐cd]PY/(indeno[1,2,3‐cd]PY + benzo[g,h,i]perylene) and several diagnostic ratios. These approaches have indicated that traffic emissions (petroleum combustion) were the dominant PAH sources at both sites for summer and winter seasons. Experimental gas–particle partition coefficients (K_P) were compared to the predictions of octanol–air (K_OA) and soot–air (K_SA) partition coefficient models. The correlations between experimental and modeled K_P values were significant (r² = 0.79 and 0.94 for suburban and urban sites, respectively, p < 0.01). Octanol‐based absorptive partitioning model predicted lower partition coefficients especially for relatively volatile PAHs. However, overall there was a relatively good agreement between the measured K_P and soot‐based model predictions.     

Modeling the Effects of Meteorological Factors on SO2 and PM10 Concentrations with Statistical Approaches

Air quality has been deteriorated seriously in urban areas as a result of increasing anthropogenic activities. Meteorological conditions affect air pollution levels in the urban atmosphere significantly due to their important role in transport and dilution of the pollutants. This paper aims to investigate usability of some promising statistical methods for examining the impacts of metrological factors on SO₂ and PM10 levels. Data were collected from city centre of Kocaeli in winter periods from 2007 to 2010 as pollutant concentrations increase in winters due to expanding combustion facilities. Results of bivariate correlation analysis showed that humidity and rainfall have remarkable negative correlations with the pollutants. Multiple linear regression models and artificial neural network (ANN) models were used to predict next day's PM10 and SO₂ levels. In regression models calculated R² values were 0.89 and 0.75 for PM10 and SO₂, respectively. Among the various architectures, single layer networks provided better performance in ANN applications. Highest R² values were obtained as 0.89 and 0.69 for PM10 and SO₂, respectively, by using appropriate networks.     

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.     

An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution

High concentrations of air pollutants in the ambient environment can result in breathing problems with human communities. Effective assessment of health-impact risk from air pollution is important for supporting decisions of the related detection, prevention, and correction efforts. However, the quality of information available for environmental/health risk assessment is often not satisfactory enough to be presented as deterministic numbers. Stochastic method is one of the methods for tackling those uncertainties, by which uncertain information can be presented as probability distributions. However, if the uncertainties can not be presented as probabilities, they can then be handled through fuzzy membership functions. In this study, an integrated fuzzy-stochastic modeling (IFSM) approach is developed for assessing air pollution impacts towards asthma susceptibility. This development is based on Monte Carlo simulation for the fate of SO₂ in the ambient environment, examination of SO₂ concentrations based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy-stochastic information. The IFSM entails (a) simulation for the fate of pollutants in ambient environment, with the consideration of source/medium uncertainties, (b) formulation of fuzzy air quality management criteria under uncertain human-exposure pathways, exposure dynamics, and SPG-response variations, and (c) integrated risk assessment under complexities of the combined fuzzy/stochastic inputs of contamination level and health effect (i.e., asthma susceptibility). The developed IFSM is applied to a study of regional air quality management. Reasonable results have been generated, which are useful for evaluating health risks from air pollution. They also provide support for regional environmental management and urban planning.     

A geostatistical approach for assessing population exposure to NO2 in a complex urban area (Beirut,Lebanon)

Few studies in the Middle East region estimated the spatial distribution of air pollutants for exposure studies. This paper presents a geostatistical approach to assess background NO₂ spatial distribution and the associated exposed population in a Mediterranean city with a complex topography, Beirut. Such modeling gave an accurate mapping of the 2010 yearly background average value of NO₂: it varies between 35 and 67 μg m^?3 with a mean of 53 μg m^?3. The mean SD of the estimated error was about 3 μg m^?3. The results showed that the spatial distribution of NO₂ follows a nested structuring, with a major structure related to topoclimatic characteristics (interaction topography/atmospheric flow at large scale) and a minor one linked to micro-environment and micro-climatic characteristics (interactions urban morphology/atmospheric flows at fine scale). The probability for the city’s inhabitants to be exposed to NO₂ levels exceeding 40 μg m^?3 threshold limit set by the World Health Organization (WHO) showed that Beirut city has a real sanitary risk to the NO₂ pollution. 93 % of the population (around 358,459 people) is 100 % sure to be exposed to a yearly average exceeding 40 μg m^?3. This knowledge will be certainly useful for developing a tool for decision support in order to implement policies of reducing air pollution in Beirut, which is, given the results, very urgent.     

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.     

Monitoring air pollution in China from geostationary satellite: A synthetic study using simulated observations

We simulated geostationary satellite observations to assess the potential for high spatial-and temporal-resolution monitoring of air pollution in China with a focus on tropospheric ozone(O_3), nitrogen dioxide(NO_2), sulfur dioxide(SO_2), and formaldehyde(HCHO). Based on the capabilities and parameters of the payloads onboard sun-synchronous satellites, we simulated the observed spectrum based on a radiative transfer model using a geostationary satellite model. According to optimal estimation theory, we analyzed the sensitivities and retrieval uncertainties of the main parameters of the instrument for the target trace gases. Considering the retrieval error requirements of each trace gas, we determined the major instrument parameter values(e.g., observation channel, spectral resolution, and signal-to-noise ratio). To evaluate these values, retrieval simulation was performed based on the three-dimensional distribution of the atmospheric components over China using an atmospheric chemical transportation model. As many as 90% of the experiments met the retrieval requirements for all target gases. The retrieval precision of total-column and stratospheric O_3 was 2%. In addition, effective retrieval of all trace gases could be achieved at solar zenith angles larger than 70°. Therefore, the geostationary satellite observation and instrument parameters provided herein can be used in air pollution monitoring in China. This study offers a theoretical basis and simulation tool for improving the design of instruments onboard geostationary satellites.     

Impacts of land-use changes on watershed discharge and water quality in a large intensive agricultural area in Thailand

The objectives of this research were to evaluate the effect of land-use change on streamflow, sediment and water quality data along the Lower Yom River, Thailand, covering an intensively agricultural area of 14 613.6 km², and to assess the relative impact of point and non-point sources of pollution from multiple-land-use watersheds. Long-term calibration and validation of the SWAT (Soil and Water Assessment Tool) model was performed on data for 2000–2013. Land-use change led to a 13–49% increase in runoff in the basin and resulted in 37–427% increased sediment yield. The amount of NO₃-N load doubled in the upper and middle parts of the study area, while the increase in PO₄^3– ranged from 37 to 377%, reflecting the increase in agricultural lands and urban areas. It is concluded that the changed land use is closely associated with the quantity of runoff, sediment yield and the NO₃-N and PO₄^3– concentrations.     

Impacts of Urbanization and Station-relocation on Surface Air Temperature Series in Anhui Province, China

Since the 1990s, many meteorological stations in China have passively “entered” cities, which has led to frequent relocation and discontinuity in observational records at many stations. To study the impacts of urbanization on surface air temperature series, 52 meteorological stations in Anhui Province were chosen based firstly on a homogeneity test of the time series, and then their surrounding underlying surfaces during different decades were identified utilizing Landsat Multispectral Scanner images from the 1970s, Landsat Thematic Mapper images from 1980s and 1990s, and Enhanced Thematic Mapper images after 2000, to determine whether or not the station “entered” city, and then these stations were categorized into three groups: urban, suburban, and rural using Landsat-measured land use/land cover (LULC) around the station. Finally, variations in annual mean air temperature (T _mean), maximum air temperature (T _max), and minimum air temperature (T _min) were analyzed in urban-type stations and compared to their surrounding rural-type stations. The results showed that, in Anhui Province over the past two decades, many rural stations experienced urbanization and changed into urban or suburban locations. This process is referred as the “city-entering” phenomena of stations. Consequently, many of the latest stations were relocated and moved to currently rural and suburban areas, which significantly influenced the continuity of observational records and the homogeneity of long-term trends. Based on homogeneous data series, the averaged annual T _mean, T _max, and T _min over Anhui Province increased at a rate of 0.407, 0.383 and 0.432 °C decade^?1 from 1970 to 2008. The strongest effect of urbanization on annual T _mean, T _max, and T _min trends occurred at urban stations, with corresponding contributions of 35.824, 14.286, and 45.161 % to total warming, respectively. This work provides convincing evidences that (1) urban expansion has important impacts on the evaluation of regional climate change, (2) high spatial resolution images of Landsat are very useful for selecting reference climate stations for evaluating the potential urban bias in the surface air temperature data in certain regions of the continents, and (3) meteorological observation adjustments of station-relocation-induced inhomogeneities are essential for the study of regional or global climate change.     

Impact of septic tank systems on local groundwater quality and water supply in the Pearl River Delta,China: case study

Located at southern coast of China, the Pearl River Delta (PRD) is facing serious water problems in both quantity and quality after its rapid urbanization in the last decade. Most remarkably, the local groundwater, that was used to be the source of drinking water before the urbanization was polluted due to poor management of the septic tanks. In order to study the effects of suburban development on local groundwater flow and water quality in the PRD region, Fengcun of Guangzhou has been chosen as the study area. In Fengcun, drinking water was groundwater before the 1990s, but now piped reservoir water is used by each family because the groundwater has been polluted. This study clarifies the source and process of the groundwater pollution from septic tanks using isotopic and geochemical characteristics, especially nitrate (NO₃^?) concentrations. Water samples were collected from the wells and ponds in Fengcun in March and July 2005 and in July 2006. Based on the pe–pH diagram, NO₃^? and ammonium of groundwater are from the effect of human activities, rather than from nitrification and ammonification of N₂. NO₃^? pollution of groundwater is from point sources, and NO₃^? concentrations decrease from northeast to southwest. Groundwater is polluted rapidly by the leakage of septic tanks. NO₃^? concentrations of pollution sources were lower than 20 mg l^?1 in March 2005, but had increased to about 120 mg l^?1 in July 2006. This implies that groundwater protection should be strengthened in rural areas of the PRD. Copyright © 2007 John Wiley & Sons, Ltd.     

The Gas-Phase Chemistry Of Urban Atmospheres

This paper reviews the chemistry of urban atmospheres,using recent measurement data to highlight the key concepts. We briefly summarise historical reports of air pollution and the impact that human activities have had on urban atmospheres since the IndustrialRevolution. Although pollution events in the first half of the 20th century were caused by high concentrations of smoke and sulphur dioxide, photochemical pollution has become the major problem in most of the major citiesaround the world. The chemistry of photochemical pollution episodes is discussed in some detail, particularly the crucial role played by volatile organic carbon and nitrogen oxides. Issues to be considered when modelling the chemistry of urban areas are briefly summarised, such as the uncertainties in chemical mechanisms and emission inventories, as well as the complexities of dynamical processes. Finally, we present some recent issues in urban chemistry, including the discovery that the amount of volatile organic carbon in urban atmospheres may be grossly under-estimated. We also use modelling resultsto show the importance of the reaction of ozone with reactive hydrocarbons as a radical source in urban atmospheres. Finally, the use of NO_X-NO₂ relationships to predict annual mean NO₂ concentrations is discussed.     

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.     

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.     

Response of surface water chemistry to reduced levels of acid precipitation: comparison of trends in two regions of New York,USA

In light of recent reductions in sulphur (S) and nitrogen (N) emissions mandated by Title IV of the Clean Air Act Amendments of 1990, temporal trends and trend coherence in precipitation (1984–2001 and 1992–2001) and surface water chemistry (1992–2001) were determined in two of the most acid‐sensitive regions of North America, i.e. the Catskill and Adirondack Mountains of New York. Precipitation chemistry data from six sites located near these regions showed decreasing sulphate (SO₄^2?), nitrate (NO₃^?), and base cation (C_B) concentrations and increasing pH during 1984–2001, but few significant trends during 1992–2001. Data from five Catskill streams and 12 Adirondack lakes showed decreasing trends in SO₄^2? concentrations at all sites, and decreasing trends in NO₃^?, C_B, and H⁺ concentrations and increasing trends in dissolved organic carbon at most sites. In contrast, acid‐neutralizing capacity (ANC) increased significantly at only about half the Adirondack lakes and in one of the Catskill streams. Flow correction prior to trend analysis did not change any trend directions and had little effect on SO₄^2? trends, but it caused several significant non‐flow‐corrected trends in NO₃^? and ANC to become non‐significant, suggesting that trend results for flow‐sensitive constituents are affected by flow‐related climate variation. SO₄^2? concentrations showed high temporal coherence in precipitation, surface waters, and in precipitation–surface water comparisons, reflecting a strong link between S emissions, precipitation SO₄^2? concentrations, and the processes that affect S cycling within these regions. NO₃^? and H⁺ concentrations and ANC generally showed weak coherence, especially in surface waters and in precipitation–surface water comparisons, indicating that variation in local‐scale processes driven by factors such as climate are affecting trends in acid–base chemistry in these two regions. Copyright © 2005 John Wiley & Sons, Ltd.     

Impacts of nutrient management and decrease in paddy field area on groundwater nitrate concentration: a case study at the Nasunogahara alluvial fan,Tochigi Prefecture,Japan

In order to help evaluate the trends in the NO₃-N concentration in groundwater with a view to preventing further degradation in water quality in the future, a distributed groundwater quality model was constructed for the Nasunogahara basin. The best fit for the groundwater table elevations by the flow component of the model was achieved with average mean absolute errors (MAEs) of 0·92 m for the calibration period and 0·83 m for the validation period. Moreover, the best fit for the NO₃-N concentration by the water quality component was achieved with average mean relative errors (MREs) of 29·8% for the calibration period and 30·3% for the validation period. After developing a robust model, various change scenarios were tested; specifically, the effects of effluent load control and a decrease in paddy field area on the NO₃-N concentration in groundwater were predicted. The most intensively farmed area contributed about 40% of the total effluent load because of livestock farming in the basin. When the effluent load from this area was decreased by 50%, the average NO₃-N concentrations at sites S1, S2 and S3 were reduced by about 15%; however, the average concentrations at S4 and S5 were reduced by only 1%. Furthermore, when the total effluent load from the concentrated livestock area was removed completely, the average groundwater NO₃-N concentrations at S1, S2 and S3 were reduced by about 30% as compared with the original calculated results. In contrast, decreasing the area of the paddy fields in the basin did not greatly influence the groundwater NO₃-N concentration. In the case of a 70% reduction in paddy field area, average NO₃-N concentrations increased by about 7% at S1, S2 and S3. Copyright © 2008 John Wiley & Sons, Ltd.     

Chemistry of Forest Fires and Regional Haze with Emphasis on Southeast Asia

— The current state of knowledge regarding the chemistry of forest fires and regional haze is reviewed. More than 100 compounds have been identified in wood smoke and many of these have also been observed in field studies. Products of biomass combustion can have different environmental effects: CO₂ and CH₄ may contribute to global warming, NO_x and SO₂ could contribute to rainwater acidity, whereas smoke particles and polynuclear aromatic hydrocarbons (PAHs) could affect human health. Also, photochemical reactions of primary emissions from biomass fires can lead to the production of secondary pollutants such as O₃. Regional haze episodes caused by forest fires have occurred in SE Asia on several occasions during the 1990s and the reported studies of these episodes are reviewed. Only total suspended particles (TSP) were determined in the earlier studies, and more comprehensive chemical investigations have only emerged during the more recent episodes, notably those of 1997 and 1998. To date, most of the measurements have centred on criteria pollutants (SO₂, NO₂, CO, O₃ and PM₁₀), however, other pollutants (e.g., VOCs, PAHs) have also been determined in certain studies. Rainwater analyses suggest that forest fires do not have a major acidifying effect because dissolved acidic gases (e.g., SO₂) are neutralised by alkaline substances (e.g., Ca, Mg, K) that are also emitted by forest fires. There is a need for further laboratory and field studies in order to investigate important pollutant transformation mechanisms.