佛山市近地面臭氧污染特征及相关气象因子分析

利用2014年佛山市8个国控大气自动监测点位的O_3监测数据,分析了佛山市的O_3污染特征,结果表明,2014年O_3日最大8 h平均值的第90百分位数为167μg/m~3,O_3为首要污染物的超标天数为43d,占比46.7%;ρ(O_3)区域变化不大;ρ(O_3)月变化呈现"三峰型",全年高ρ(O_3)集中在6—10月份,其中7月份出现全年最高峰值;ρ(O_3)日变化呈单峰型分布,夜间浓度较低且变化平缓,14:00—16:00左右达到峰值,并存在一定的"周末效应",但并不明显;ρ(O_3)与气温呈显著正相关,与湿度、气压、雨量呈显著负相关,与风向、风速的相关性相对较弱;总体上看,高温、低湿、微风、偏南风、低压、无雨的天气条件下高ρ(O_3)更容易出现。     

Eco-hydrodynamic Modelling of Chini Lake: Model Description

In this study, we coupled a three-dimensional hydrodynamic model with an ecosystem model and applied it to the shallow complex floodplain wetland of Chini Lake in Malaysia. Our objective was to provide a better understanding of the lake’s ecosystem dynamics under different forcing mechanisms. Simulations and validation were performed over a dry month period. Wind speed ranged between 0 and 7.7 m s^?1, whilst air temperature ranged between 22.0 and 35.6 °C. Advective transport driven by wind stress was the dominant physical force that shaped the water quality variations during the dry season. Convective circulation intermittently influenced the circulation during calm conditions. Nutrient concentration and stratification of dissolved oxygen (DO) varied between the lakes. Wind events saw patterns of the surface DO concentrations move spatially in the direction of the wind. The ecosystem model simulation suggested that the water quality in Chini Lake was influenced by macrophyte production, although the dissolved and particulate organic carbon accounted for the major fraction of organic matter content in the lake.     

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.     

Mathematical representation of short term phosphorus variations in a non-stratified southern lake

Total phosphorus concentrations in a small urban hypereutrophic lake undergoing restoration were continually modeled by a modified version of a Vollenweider model for the latter part of a three and one-quarter year restoration period. Results of the modeling effort on Crest Lake were analyzed to determine the compatibility of the basic Vollenweider model with short term applications to highly eutrophic southern lakes. Input parameters such as rainfall and wind speed were considered on a daily basis to see if the model could represent the short term variations observed in the lake. Model simulations were compared to total phosphorus observations collected on the lake at intervals as short as one day. Results indicated that the model can be used as a tool for analysis of system responses on a seasonal basis, but short term variations on the weekly or daily timeframe were poorly represented by the model. Intensive temporal and spatial sampling within the lake verified the validity of the completely mixed assumption for short term applications. Nine sampling locations within the lake, distributed with area and depth, displayed a mean coefficient of variation of only 10.9% when averaged daily for the 54 day intense sampling period. Short term variations were poorly correlated with meterological inputs, suggesting that variability be best represented by a stochastic approach if a practical management tool is desired for situations where variability is critical. The seasonal trends were well represented by the model, reflecting the rapid response of hypereutrophic systems to alterations in phosphorus loadings.     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

Modelling the Effect of Weather Conditions on Cyanobacterial Bloom Outbreaks in Lake Dianchi: a Rough Decision-Adjusted Logistic Regression Model

Lake Dianchi, one of the main water sources for Kunming, China, experiences severe cyanobacterial blooms due to rapid urbanization and local industrial development. Scientific interest in the mechanisms that cause blooms has been increasing. An integrated model combining rough set theory with binary logistic regression was used to examine the correlation between weather conditions and cyanobacterial blooms in Lake Dianchi based on daily monitoring data. The binary logistic regression yielded quantitative correlations between cyanobacterial blooms and the assessed meteorological variables, including temperature, wind velocity, and wind direction. The rough decision process connected the weather conditions and cyanobacterial blooms, which were used to verify the binary regression model results. It was shown that by comparing the methods, the rough decision-adjusted binary logistic regression model significantly improved model accuracy. The integrated model of cyanobacterial blooms in Lake Dianchi may inform decision-makers at local water purification plants of the water quality in the lake and assist them in making more cost-effective decisions.     

洞庭湖区一次重度空气污染过程成因分析

利用AQI和PM_(2. 5)质量浓度、地面气象要素、NCEP、ERSST_V3、GBL等资料,对2016年12月29日至2017年1月5日洞庭湖区一次重度空气污染过程成因进行了分析。结果表明,静稳天气形势下的累积效应和本地持续升温、降压、增湿、小风导致污染物浓度不断增加。本地风速与雨量对污染物浓度产生显著影响。降温前风速明显加大,有利于污染物快速扩散。湿度增加有利于污染物吸湿性增长,但高湿易引起降水有利于污染物的湿清除。此次重度空气污染过程中大气稳定度为中性或稳定,14:00混合层高度逐渐降低且重度空气污染日降至100 m以下。污染物空间分布与主导风向和污染通道密切相关。气流后向轨迹分析表明,洞庭湖区各地气流来源和影响路径差异明显,且存在大范围区域性同步污染现象。北方外来污染源是洞庭湖区重要的污染面源,本地工业污染排放点源和地理条件也是洞庭湖区空气污染物空间分布差异的重要因素。     

The effects of season and sand mining activities on thermal regime and water quality in a large shallow tropical lake

Thermal structure and water quality in a large and shallow lake in Malaysia were studied between January 2012 and June 2013 in order to understand variations in relation to water level fluctuations and in-stream mining activities. Environmental variables, namely temperature, turbidity, dissolved oxygen, pH, electrical conductivity, chlorophyll-A and transparency, were measured using a multi-parameter probe and a Secchi disk. Measurements of environmental variables were performed at 0.1 m intervals from the surface to the bottom of the lake during the dry and wet seasons. High water level and strong solar radiation increased temperature stratification. River discharges during the wet season, and unsustainable sand mining activities led to an increased turbidity exceeding 100 NTU, and reduced transparency, which changed the temperature variation and subsequently altered the water quality pattern.     

Water quality monitoring and assessment of an urban Mediterranean lake facilitated by remote sensing applications

Degradation of water quality is a major problem worldwide and often leads to serious environmental impacts and concerns about public health. In this study, the water quality monitoring and assessment of the Koumoundourou Lake, a brackish urban shallow lake located in the northeastern part of Elefsis Bay (Greece), were evaluated. A number of water quality parameters (pH, temperature, dissolved oxygen concentration, electrical conductivity, turbidity, nutrients, and chlorophyll-a concentration) were analyzed in water samples collected bimonthly over a 1-year period from five stations throughout the lake. Moreover, biological quality elements were analysed seasonally over the 1-year period (benthic fauna). Statistical analysis was performed in order to evaluate the water quality of the lake and distinguish sources of variation measured in the samples. Furthermore, the chemical and trophic status of the lake was evaluated according to the most widely applicable classification schemes. Satellite images of Landsat 5 Thematic Mapper were used in order for algorithms to be developed and calculate the concentration of chlorophyll-a (Chl-a). The trophic status of the lake was characterized as oligotrophic based on phosphorus and as mesotrophic–eutrophic based on Chl-a concentrations. The results of the remote sensing application indicated a relatively high coefficient of determination (R ²) among point sampling results and the remotely sensed data, which implies that the selected algorithm is reliable and could be used for the monitoring of Chl-a concentration in the particular water body when no field data are available.     

Origin and spatial–temporal distribution of faecal bacteria in a bay of Lake Geneva, Switzerland

The origin and distribution of microbial contamination in Lake Geneva's most polluted bay were assessed using faecal indicator bacteria (FIB). The lake is used as drinking water, for recreation and fishing. During 1 year, water samples were taken at 23 points in the bay and three contamination sources: a wastewater treatment plant (WWTP), a river and a storm water outlet. Analyses included Escherichia coli, enterococci (ENT), total coliforms (TC), and heterotrophic plate counts (HPC). E. coli input flux rates from the WWTP can reach 2.5 x 10(10) CFU/s; those from the river are one to three orders of magnitude lower. Different pathogenic Salmonella serotypes were identified in water from these sources. FIB levels in the bay are highly variable. Results demonstrate that (1) the WWTP outlet at 30 m depth impacts near-surface water quality during holomixis in winter; (2) when the lake is stratified, the effluent water is generally trapped below the thermocline; (3) during major floods, upwelling across the thermocline may occur; (4) the river permanently contributes to contamination, mainly near the river mouth and during floods, when the storm water outlet contributes additionally; (5) the lowest FIB levels in the near-surface water occur during low-flow periods in the bathing season.     

特殊风场条件对太湖蓝藻水华迁移的影响研究

在高温、微风气象条件下,适宜蓝藻水华形成。在特殊非均一风场的驱动下,太湖蓝藻水华迁移过程与被均匀风场驱动有所不同。选取太湖典型风向进行分析,并采用三维水动力水质模型对表面非均一风场条件下的风生流流场及水质进行模拟,结果表明,在特殊非均一风场的驱动下,当太湖蓝藻浓度较高时,容易在西部湖区特别在竺山湖、梅梁湾湾内、岸边及湾口聚集,形成水华暴发,这有助于研究太湖污染物及蓝藻水华的输移及空间分布和机理。     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

Morphological characterization of suspended particles under wind-induced disturbance in Taihu Lake, China

Sediments are disturbed by wind frequently, especially in the shallow lakes. The characteristics of resuspended sediment particles in Taihu Lake were studied under different wind velocities. It showed that sediment particles suspended obviously and particle number in overlying water increased directly under high wind-induced disturbance. Suspended solid (SS) concentration was less than 50 mg/l when the wind velocity was below 3.0 m/s, however, it increased to more than 300 mg/l when the wind velocity was 10.0 m/s. Two methods were used to measure the fractal characteristics of particles. One was light scattering and the other was image analysis. The three-dimensional fractal dimensions of suspended particles, measured by light scattering, were between 2.26 and 2.44; correspondingly, the two-dimensional fractal dimensions, calculated by image analysis, were between 1.44 and 1.77. Moreover, the three-dimensional fractal dimensions were directly proportional to two-dimensional fractal dimensions. The characteristic length of particles was calculated by image analysis. The minimum characteristic length was close to 8.5 μm when the wind velocity was 1.5 m/s at 50 cm beneath lake surface, while, the maximum characteristic length was approximate to 24 μm when the wind velocity was 10 m/s at the depth of 150 cm.     

Assessing the risk posed by high-turbidity water to water supplies

The objective of this study is to assess the risk of insufficient water supply posed by high-turbidity water. Several phenomena can pose risks to the sufficiency of a water supply; this study concerns risks to water treatment plants from particular properties of rainfall and raw water turbidity. High-turbidity water can impede water treatment plant operations; rainfall properties can influence the degree of soil erosion. Thus, water turbidity relates to rainfall characteristics. Exceedance probabilities are presented for different rainfall intensities and turbidities of water. When the turbidity of raw water is higher than 5,000 NTU, it can cause operational problems for a water treatment plant. Calculations show that the turbidity of raw water at the Ban-Sin water treatment plant will be higher than 5,000 NTU if the rainfall intensity is larger than 165 mm/day. The exceedance probability of high turbidity (turbidity >5,000 NTU) in the Ban-Sin water treatment plant is larger than 10%. When any water treatment plant cannot work regularly, its ability to supply water to its customers is at risk.     

Spatial and temporal dynamic of trophic relevant parameters in a subtropical coastal lagoon in Brazil

Coastal lagoons are ecologically and economically important environments but a relative low number of studies were carried out in subtropical and permanently closed coastal lagoons. The present study aimed at assessing the temporal and spatial dynamic of trophic relevant water quality parameters in the small, deep and freshwater Peri coastal lagoon, South Brazil. During the 19 sampled months (March/2008-September/2009) spatial homogeneity (horizontal and vertical) was registered in all seasons for all variables, a condition related to the strong wind influence and low human occupation in the lagoon watershed. Seasonal variations of the water quality could be observed and they can be explained mainly by variation on temperature, wind forces and direction and rainfall, characteristic from the subtropical weather. Comparing this study with two others conducted in Peri lagoon in 1996 and 1998, no critical differences that evidence alteration in the water quality were found, but climate differences may have influenced in some small variations observed. The use of four trophic state indices indicated that indices designed for temperate lakes are inappropriate for the subtropical Peri lagoon. The lagoon was classified as oligotrophic for nutrients concentrations and meso-eutrophic for transparency and chlorophyll-a, which can be explained by the high densities and monodominance of the cyanobacterium Cylindrospermopsis raciborskii and the high recycling rates observed in warmer water bodies, when compared to the temperate ones.     

Bacterial community composition of sediments from Artificial Lake Maslak, Istanbul, Turkey

Small artificial lakes are ubiquitous in various natural environments. Small impoundments increase the residence time of water, thereby increasing the potential for retention of nutrients through biological and physical processes. We examined bacterial community structure of Lake Maslak, a small freshwater impoundment located in a densely populated region. The objective of our study was to investigate bacterial communities of the lake sediment which has not been determined and to elucidate the factors controlling bacterial diversity and the biogeochemical processes within the lake. For these purposes, surface water, lake bed sediments, and one core sample were collected. Microbiological characteristic of the lake bed and core sediments was determined by denaturing gradient gel electrophoresis targeting the 16S rRNA gene. Along with the microbiological studies, physicochemical (O(2), pH, temperature) and geochemical properties of the surface (NO (3) (-) , NO (2) (-) , NH (4) (+) ,PO (4) (-) ,SO (4) (2-) , K(+), Mg(2+), Ca(2+)) and pore water (K(+), Mg(2+), Ca(2+)) were determined in addition to heavy metals contents (Co Cu, Fe, Zn, Pb, Cd). Eight lake bed and one core sediments were also collected and analyzed for heavy metals and elemental compositions. Nitrate concentration in the surface water ranges from 0.27-1.8 mg/L, and ammonium (0.0-0.83 mg/L) appears to follow nitrate concentration. Sulfate concentration in the surface water (mean 60 mg/L) is greater than those measured in the pore water (mean, 37.5 mg/L). Fe, Zn, Pb, and Cd were not determined in the surface water, whereas Co was significantly higher both in the surface and pore water. Unlike Co, Pb, Zn, and Cd were not measured in the pore water. Lakebed and core sediments show significant enrichment in Pb, Zn, and Cu, indicating anthropogenic pollution. Consistent with geochemical parameters, microbiological analysis suggests a diverse bacterial community in the lake sediments and influence of anthropogenic pollution (e.g., atmospheric emission) on bacterial community.     

Carbon Monoxide Concentration in a Street Canyon of Buenos Aires City (Argentina)

The analysis of three years of 8-h CO concentration values registered in a deep street canyon downtown shows high frequency of values that exceed WHO health protection guidelines. An inverse relationship between opposing percentiles of the distributions of CO concentrations and mean wind speed could be found. Data also showed a variation of mean CO values with prevailing wind direction. The averaged concentration value obtained when the sampler probe is on the leeward side is lower than the obtained when it is on the windward wall. A preliminary explanation of this feature may be related to the advection of polluted air from a high traffic density area nearby.     

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.     

Computational Fluid Dynamics Modelling of the Pollution Dispersion and Comparison with Measurements in a Street Canyon in Helsinki

A measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki in 2003–2004. The concentrations of NO _x , NO₂, PM₁₀ and PM_2.5 were measured at street level and at roof level at an urban background location. This study utilises the data measured from 1 Jan to 30 April, 2004, when wind speed and direction measurements were also conducted on-site at the roof level. The computational fluid dynamics model ADREA-HF was used to compute the street concentrations, and the results were compared with the measurements. The predictions for the selected cases agreed fairly well (within < 25 % for 15 min average values) with the measured data, except for two cases: a windward flow in case of a low wind speed, and a moderate southerly flow parallel to the street canyon. The main reasons for the differences of predictions and measurements are the negligence of traffic-induced turbulence in the modelling and an under-prediction of ventilation of urban background air from a crossing street. Numerical results are presented for various example cases; these illustrate the formation of the vortices in the canyon in terms of the wind direction and speed and the influence of the characteristics of the flow fields on the concentration distributions.     

Modelling the Effects of Inflow Parameters on Lake Water Quality

A one-dimensional lake water quality model which includes water temperature, phytoplankton, phosphorus as phosphate, nitrogen as ammonia, nitrogen as nitrate and dissolved oxygen concentrations, previously calibrated for Lake Calhoun (USA) is applied to Uokiri Lake (Japan) for the year 1994. The model simulated phytoplankton and nutrient concentrations in the lake from July to November. Most of the water quality parameters are found to be the same as for Lake Calhoun. To predict probable lake water quality deterioration from algal blooming due to increased nutrient influx from river inflow, the model was run for several inflow water conditions. Effects of inflow nutrient concentration, inflow volume, inflow water temperatures are presented separately. The effect of each factor is considered in isolation although in reality more than one factor can change simultaneously. From the results it is clear that inflow nutrient concentration, inflow volume and inflow water temperature show very regular and reasonable impacts on lake water quality.