Application of multivariate statistical techniques in assessment of surface water quality in Second Songhua River basin,China

Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.

Impacts of Climate Change on Water Resources in Diyala River Basin, Iraq

Diyala River is the third largest tributary of the Tigris River running 445 km length and draining an area of 32,600 km2. The river is the major source of water supply for Diyala City for municipal, domestic, agriculture and other purposes. Diyala River Basin currently is suffering from water scarcity and contamination problems. Up-to-date studies have shown that blue and green waters of a basin have been demonstrating increasing variability contributing to more severe droughts and floods seemingly due to climate change. To obtain better understanding of the impacts of climate change on water resources in Diyala River Basin in near 2046-2064 and distant future 2080~2100, SWAT （soil and water assessment tool） was used. The model is first examined for its capability of capturing the basin characteristics, and then, projections from six GCMs （general circulation models） are incorporated to assess the impacts of climate change on water resources under three emission scenarios： A2, AIB and B1. The results showed deteriorating water resources regime into the future.

Integrated evaluation system under randomness and fuzziness for groundwater contamination risk assessment in a little town, Central China

An integrated evaluation system under randomness and fuzziness was developed in this work to systematically assess the risk of groundwater contamination in a little town, Central China. In this system, randomness of the parameters and the fuzziness of the risk were considered simultaneously, and the exceeding standard probability of contamination and human health risk due to the contamination were integrated. The contamination risk was defined as a combination of "vulnerability" and "hazard". To calculate the value of "vulnerability", pollutant concentration was simulated by MODFLOW with random input variables and a new modified health risk assessment(MRA) model was established to analyze the level of "hazard". The limit concentration based on environmental-guideline and health risk due to manganese were systematically examined to obtain the general risk levels through a fuzzy rule base. The "vulnerability" and "hazard" were divided into five categories of "high", "medium-high", "medium", "low-medium" and "low", respectively. Then, "vulnerability" and "hazard" were firstly combined by integrated evaluation. Compared with the other two scenarios under deterministic methods, the risk obtained in the proposed system is higher. This research illustrated that ignoring of uncertainties in evaluation process might underestimate the risk level.

Estimation of Transported Pollutant Load from Small Urban Kahuwa River Micro-catchment in Lake Kivu, Democratic Republic of Congo

This study estimated pollutant load from Kahuwa micro-catchment into Lake Kivu. The micro-catchment was sampled monthly for a year at six locations to capture the contribution of agricultural land, industries and commercial blocks. Both wet and dry depositions in terms of TN （total nitrogen） and TP （total phosphorus） were estimated monthly. The level of pollution was estimated using LISEC index and IPO （organic pollution indices）. Results show that Kahuwa River micro-catchment is polluted mainly by waste dumping sites and industries within the micro-catchment. The general load to the outlet was respectively about 0.35 tons per year （t/yr） for BODs, 1.9 t/yr for COD, 32.73 t/yr for TP and 224.37 t/yr for TN. Atmospheric deposition of nutrient contributed for about 4% and 18% of TP, 3% and 0.01% of TN during dry and wet deposition, respectively.

Study on Pollution Level and Sources Distribution of Polychlorinated Naphthalenes in City Sewage

Polychlorinated naphthalene （PCNs） have similar structure and toxicity with dioxin class （PCDD/Fs）, it can be detected in the global environmental and biological samples. This paper introduces the main sources of PCNs in the environment and environmental fate, introduced emphasis with the emission characteristics of PCNs in burning and metal smelting process, this article summarized the current PCNs city environmental and biotic pollution level and distribution characteristics, summarized and discussed related research of PCNs pollution level and distribution characteristics near the various environmental media and organisms in the city. Finally, the paper put forward the research progress of PCNs in related research areas and challenges.

Characteristics of integrated biological aerated filter in municipal wastewater treatment

In this paper, the characteristics of integrated biological aerated filter (IBAF) applied to municipal wastewater treatment were studied in a pilot scale experiment. The experimental results showed that IBAF has high efficiencies in removing organic pollutants, such as CODCr and SS, in municipal wastewater. The removal rates of CODCr and SS can reach over 90% and 80%, respectively, when COD and SS in the influent are 234 mg L1 and 112 mg L1, hydraulic retention time (HRT) is 8 h, and the aerated intensity is in the range of (0.5 to 0.6) L m2 s1.

Adsorption characteristics of construction waste for heavy metals from urban stormwater runoff

Stormwater runoff has become an important source of surface water pollution. Bioretention, a low impact development measure in urban stormwater management, has been proven to be effective in the removal of pollutants from stormwater runoff, with appropriate bioretention media. In this study, construction wastes were selected as bioretention media to remove heavy metals from stormwater runoff. Static and dynamic adsorption batch experiments were carried out to investigate the adsorption of heavy metals in simulated stormwater runoff system with construction wastes in different particle sizes. The experimental results show that the pseudo-secondorder kinetic model characterizes the adsorption process and the adsorption equilibrium data are well described by Freundlich isotherm model. The construction wastes used can remove heavy metals from stormwater runoff effectively, with their average removal rates all more than 90%. The particle size of construction wastes greatly influences the equilibrium time, rate and adsorption capacity for heavy metals.

Gross Pollutants Study in Urban Areas under Tropical Climates

Gross pollutants are the primary targeted pollutants in urban catchment management for urban water quality improvement as well as mitigation of flood. Apart from aesthetically unattractive because of its visibility, gross pollutants also contributes to degradation of river water quality and loss of aquatic habitat as it carries harmful pollutants such as oxygen demanding material, hydrocarbons and heavy metals. This study analyzed trend of gross pollutant generated from two urban residential areas located in Selangor, Malaysia. The median value of gross pollutant load obtained fi＇om the Amanah Apartment and Bandar Botanic are 347.41 kg/ha/year and 32.46 kg/ha/year, respectively. Relationship between gross pollutant wet load with rainfall depths was derived using regression equation. A significant trend of increasing gross pollutant wet load into drainage system with increasing rainfall depth was observed. The behavior of pollutant load is related to the one observed in Australia.

Data Dependent Modeling of New Contamination Cases from Urban Historic Groundwater Records

Groundwater is the water located beneath the earth＇s surface in the soil pore spaces and in the fractures of rock formations. As one of the most important natural resources, groundwater is associated with the environment, public health, welfare, and long-term economic growth, which affects the daily activities of human beings. In modern urban areas, the primary contaminants of groundwater are artificial products, such as gasoline and diesel. To protect this important water resource, a series of efforts have been exerted, including enforcement and remedial actions. Each year, the TGPC （Texas Groundwater Protection Committee） in US publishes a ＂Joint Groundwater Monitoring and Contamination Report＂ to describe historic and new contamination cases in each county, which is an important data source for the design of prevention strategies. In this paper, a DDM （data dependent modeling） approach is proposed to predict county-level NCC （new contamination cases）. A case study with contamination information from Harris County in Texas was conducted to illustrate the modeling and prediction process with promising results. The one-step prediction error is 1.5%, while the two-step error is 12.1%. The established model can be used at the county-level, state-level, and even at the country-level. Besides, the prediction results could be a reference during decision-making processes.

Microbial aerosol characteristics in highly polluted and nearpristine environments featuring different climatic conditions

There is an increasing interest in understanding ambient bioaerosols due to their roles both in health and in climate. Here, we deployed an Ultraviolet Aerodynamic Particle Sizer to monitor viable （fluorescent） bioaerosol concentration levels at city centers （highly polluted） and their corresponding suburbs （near pristine） （total 40 locations） in 11 provinces featuring different climate zones in China between July 16 and 28, 2013. The concentration levels of viable bioaerosol particles （BioPM） of 〉0.5 μm were measured, and corresponding percentages of BioPM% （biological fraction of total PM） and BioPM2.5% （biological fraction of PM2.5） in particulate matter （PM） and BioPM, respectively, were determined. For some key cities, indoor viable bioaerosol levels were also obtained. In addition, bacterial structures of the air samples collected across these monitoring locations were studied using pyrosequencing. BioPM concentration levels ranged from 2.1 ×10^4 to 2.4 × 10^5/m3 for city centers [BioPM% = 6.4 % （4-6.3 %）] and 0.5 × 10^4 to 4.7 × 10^5/m3 for suburbs [BioPM% = 10 % （4-8.7 %）]. Distinctive bioaerosol size distribution patterns were observed for different climate zones, e.g., some had fluorescence peaks at 3 μm, while the majority had peaks at 1 μm. Ambient bacterial aerosol community structures were also found different for different geophysical locations. Results suggest that there was a poor overall relationship between PM and BioPM across 40 monitoring locations （R2= 0.081, two-tailed P value = 0.07435）. Generally, city centers had higher PM concentrations than suburbs, but not BioPM and BioPM%. Indoor bioaerosol levels were found at least tenfold higher than those corresponding outdoors. Bacillus was observed to dominate the bacterial aerosol community in the air sample.