Regional and Temporal Differences in Nitrate Trends Discerned from Long‐Term Water Quality Monitoring Data

Riverine nitrate (NO₃) is a well‐documented driver of eutrophication and hypoxia in coastal areas. The development of the elevated river NO₃ concentration is linked to anthropogenic inputs from municipal, agricultural, and atmospheric sources. The intensity of these sources has varied regionally, through time, and in response to multiple causes such as economic drivers and policy responses. This study uses long‐term water quality, land use, and other ancillary data to further describe the evolution of river NO₃ concentrations at 22 monitoring stations in the United States (U.S.). The stations were selected for long‐term data availability and to represent a range of climate and land‐use conditions. We examined NO₃ at the monitoring stations, using a flow‐weighting scheme meant to account for interannual flow variability allowing greater focus on river chemical conditions. River NO₃ concentration increased strongly during 1945‐1980 at most of the stations and have remained elevated, but stopped increasing during 1981‐2008. NO₃ increased to a greater extent at monitoring stations in the Midwest U.S. and less so at those in the Eastern and Western U.S. We discuss 20th Century agricultural development in the U.S. and demonstrate that regional differences in NO₃ concentration patterns were strongly related to an agricultural index developed using principal components analysis. This unique century‐scale dataset adds to our understanding of long‐term NO₃ patterns in the U.S.     

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

Nonpoint source pollution is the leading cause of the U.S.’s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO₃NO₂-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO₃NO₂-N concentration and predict NO₃NO₂-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO₃NO₂-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO₃NO₂-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO₃NO₂-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution.     

The impact of urban growth on regional air quality surrounding the Langat River Basin, Malaysia

Studies of air quality were carried out in the towns of Kajang, Nilai and Banting in the Langat River Basin, southern region of Kuala Lumpur to determine the status and trend of air quality. The determination of air quality was based on several parameters such as suspended solids with diameters less than 10???m (PM₁₀) and gaseous pollutants of sulphur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO). Primary concentration data of air pollutants were compiled through fieldwork studies and combined with secondary data obtained from the regular monitoring data as collected by Alam Sekitar Malaysia Sdn. Bhd. (ASMA) on behalf of Malaysian Department of Environment (DOE) at their stations in Kajang and Nilai. Results showed that the average concentrations of PM₁₀, SO₂, NO₂, O_3, and CO at all sampling stations were still below the permissible values recommended by the Malaysian DOE. The level of gaseous pollutants of NO₂, O_3, and CO was recorded at statistically higher levels (p?<?0.05) than values recorded at the control station at Pangsun Recreational Area. These pollutants were suspected to have originated mainly from exhaust systems of motor vehicles. Data for the years 1996 to 2006 as obtained from ASMA showed long-term air quality trends of increasing O₃ and NO₂ concentrations in Kajang whilst concentrations of PM₁₀ recorded at both Kajang and Nilai stations were mostly expected coming from transboundary sources especially biomass burning and the development activities around the study areas.     

长沙市空气自动站周边区域大气污染物排放源清单

以长沙市空气自动站周边3 km为研究对象,基于统计年鉴和实地调查,获得了该地区2015年储存运输源、废弃物处理源、工艺过程源、化石燃料固定燃烧源、农业源、生物质燃烧源、扬尘源、移动源8个源类的活动水平数据。以大气污染物排放源清单编制技术指南为依据,建立了2015年长沙市空气自动站周边3 km区域NH_3、NO_x、PM_(10)、PM_(2.5)、SO_2、VOCs等6项污染物的源排放清单。结果表明,2015年长沙空气自动站周边3 km内,8类大气污染源排放的NH_3、NO_x、PM_(2.5)、PM_(10)、SO_2、VOCs总量分别为53.65t、4 899.35t、1 846.09t、6 257.75t、989.49t、4 383.31t。NH_3、NO_x、PM_(2.5)、PM_(10)、SO_2、VOCs排放量最大的源分别是农业源、移动源、扬尘源、扬尘源、化石燃料固定燃烧源和移动源,贡献率分别为98.45%、84.24%、60.82%、85.90%、97.33%、49.88%。优化道路交通、减少燃煤、减少建筑工地扬尘排放可促进长沙市空气自动站周边空气质量改善。     

Surface water quality and its control in a river with intensive human impacts–a case study of the Xiangjiang River,China

Surface water quality and its natural and anthropogenic controls in the Xiangjiang River were investigated using multivariate statistical approaches and a comprehensive observation dataset collected from 2004 to 2008. Cluster analysis (CA) grouped the 15 different sampling stations into five clusters with similar hydrochemistry characteristics and pollution levels. Four principal components (PCs), nutrients, heavy metals, natural components, and organic components, were extracted from the entire dataset. Comparison of the different regional characteristics of these four PCs revealed a decreasing trend for heavy metals and an increasing trend for organic factor on an annual scale, and the seasonal trend was only observed for natural factor. We also conducted analysis of variance (ANOVA) in combination with principal component analysis (PCA) to quantify the relative contribution of spatial and temporal variations to each of the four PCs. The results revealed that 62% of the contributions from the spatial sites were responsible for variations in heavy metals, while 83% of the contributions from the sampling time were responsible for natural variations observed. However, no significant spatial or temporal contributions were found to be responsible for the nutrient and organic variations. Finally, some suggestions regarding water management were put forward based on the current status and future trends of surface water quality in the Xiangjiang River.     

《大气污染防治行动计划》实施环境效果模拟

本研究利用2010年污染源普查数据和MEIC排放清单建立全国大气污染物高时空分辨率排放清单,在此基础上利用2012年环境统计数据对其进行修订建立2012年全国大气污染物高时空分辨率排放清单;结合《大气污染防治行动计划》(以下简称《计划》)研究工作,测算了《计划》实施后在污染源综合治理、落后产能淘汰、能源结构调整方面对SO2、NOx、颗粒物、VOCs的减排量,同时对污染物新增量进行了预测,建立了《计划》实施后全国大气污染物高时空分辨率排放清单;利用CMAQ空气质量模型模拟分析了《计划》实施的空气质量改善效果。结果表明:《计划》实施后,将可以减少641万吨SO2、859万吨NOx、547万吨颗粒物(不含扬尘污染控制)、627万吨VOCs,全国、京津冀、长三角及珠三角区域PM2.5年均浓度将分别比2012年下降22.08%、33.99%、23.98%、24.04%。如果《计划》要求全部落实,可以实现空气质量改善目标。     

Impacts on air pollution in urban areas

Environmental management involves controlling various forms of pollution to levels that do not pose a threat to the health of the people and the environment in general. This paper presents a framework to analyze sources of local air pollution in cities. Using an OLS model, an investigation is performed of the relationship among the concentrations of air pollutants [more precisely, concentrations of sulfur dioxide (SO₂), dust, nitric oxide (NO), nitrogen dioxide (NO₂), carbon oxide (CO) and ozone (O₃)], economic activities, and meteorology. Time series analysis leads to a model, that explains a high degree of the variance in the air pollution data. The model is applied to daily time series from three measurement stations in innsbruck, Austria. Estimation results of the model generally fit with the expected relations. Space heating influences SO₂, dust, and NO, while NO₂ levels are primarily affected by traffic. These results also indicate interdependent relations among the pollutants NO, NO₂, O₃, and CO; O₃ levels depend on temperature and sunshine.     

Fertilizer Management in Watersheds of Two Ramsar Wetlands and Effects on Quality of Inflowing Water

Two field experiments were carried out in the watersheds of two Ramsar wetland areas, Lakes Koronia and Volvi (area A) and Lakes Mikri and Megali Prespa (area B), to study the effect of application of N fertilizer on wheat yields, the quality of runoff water, and the quality of stream water. The treatments were a combination of two methods of fertilizer application (total amount in fall, and 2/3 in fall + 1/3 in spring) at three rates (0, 100, and 200 kg N/ha) with four replications. Concentrations of NH₄ ⁺, NO₃ ⁻, NO₂ ⁻, P, and Cl⁻ and pH were determined in all water samples. Runoff water quality was not influenced by fertilizer application in either area. Chemical parameters for water did not differ along the selected watercourses in area B, while in area A they were higher in the samples taken near Lake Koronia than in the samples taken upstream, indicating that the watercourses are polluted downstream by nonagricultural sources. The differences in wheat yields between the 100 and 200 kg N/ha application rates were not high. These results call for better fertilizer management in order to achieve better yields and to diminish the possibility to have negative effects to the environment.     

Assessment of the spring water quality in The Shoubak area,Jordan

The present study investigates the physical, chemical, and biological characteristics of spring water samples in Shoubak area in the southern Jordan. The samples were collected from May 2004 to May 2005. All samples were analyzed for temperature, conductivity, dissolved oxygen, pH, major cations (Ca²⁺, Mg²⁺, K⁺, Na⁺), major anions (Cl⁻, NO₃⁻, HCO₃⁻, SO₄²⁻, PO₄³⁻, F⁻), and trace metals (Fe²⁺, Al³⁺, Mn²⁺, Cu²⁺, Cr³⁺, Ni²⁺, Zn²⁺, Pb²⁺, Cd²⁺). Water quality for available springs showed high salinity through long period of contact with rocks. The ion concentrations in the water samples were from dissolution of carbonate rocks and ion exchange processes in clay. The general chemistry of water samples was typically of alkaline earth waters with prevailing bicarbonate chloride. Some springs showed elevated nitrate and sulfate contents which could reflect to percolation from septic tanks, cesspools, and agricultural practices. The infiltration of wastewater from cesspools and septic tanks into groundwater is considered the major source of water pollution. The results showed that there were great variations among the analyzed samples with respect to their physical, chemical and biological parameters, which lie below the maximum permissible levels of the Jordanian and WHO drinking water standards. The results indicate that the trace metals of spring’s water of Shoubak area do not generally pose any health or environmental problems. Factor analysis was used to identify the contributers to water quality. The first factor represents major contribution from anthropogenic activities, while the second one represents major contribution from natural processes.     

Evaluation of spatial and temporal variation in Karun River water quality during five decades (1968–2014)

In the present study, the multivariate statistical technique cluster analysis (CA) is used to evaluate the spatial and temporal variations in the water quality data for the Karun River, which was gathered during 46 years of monitoring (from 1968 to 2014). The data recorded electrical conductivity (EC) in the river at six water monitoring stations along its course. The mean of EC was 972.05 ± 365.466 micromhos per centimeter (μmhos/cm) at the most upstream station and showed an increase to 1458.41 ± 675.048 μmhos/cm at the most downstream of the stations. By using hierarchical CA, the six sampling stations were grouped into three clusters of similar characteristics, which may be a result of different land uses in proximity to the stations. Furthermore, two‐way analysis of variance showed that EC had a significant correlation (p < 0.001) with the season, and the mean of the pollution depended on the level of the cluster and the season (spring, summer, autumn, and winter).     

Environmental Control and Limnological Impacts of a Large Recurrent Spring Bloom in Lake Washington,USA

A series of statistical analyses were used to identify temporal and spatial patterns in the phytoplankton and nutrient dynamics of Lake Washington, an mesotrophic lake in Washington State (USA). These analyses were based on fortnightly or monthly samples of water temperature, Secchi transparency, ammonium (NH₄), nitrate (NO₃), inorganic phosphorus (IP), total nitrogen (TN), total phosphorus (TP), dissolved oxygen (DO), pH and chlorophyll a (chl a) collected during 1995–2000 from 12 stations. Lake Washington has a very consistent and pronounced annual spring diatom bloom which occurs from March to May. During this bloom, epilimnetic chl a concentrations peak on average at 10 μg/L, which is 3 times higher than chl a concentrations typically seen during summer stratified conditions. The spring bloom on average comprised 62% diatoms, 21% chlorophytes and 8% cyanobacteria. During summer stratification, diatoms comprised 26% of the phytoplankton community, chlorophytes 37% and cyanobacteria 25%. Cryptophytes comprised approximately 8% of the community throughout the year. Overall, 6 phytoplankton genera (i.e., Aulacoseira, Fragilaria, Cryptomonas, Asterionella, Stephanodiscus, and Ankistrodesmus) cumulatively accounted for over 50% of the community. These analyses also suggest that the phytoplankton community strongly influences the seasonality of NO₃, IP, DO, pH and water clarity. According to a MANOVA, seasonal fluctuations explained 40% of the total variability for the major parameters, spatial heterogeneity explained 10% of variability, and the seasonal-spatial interaction explained 10% of variability. Distinctive patterns were identified between offshore and inshore sampling stations. The results of our analyses also suggest that spatial variability was substantial, but much smaller than temporal variability.     

Application of Multivariate Statistical Methods and Water-Quality Index to Evaluation of Water Quality in the Kashkan River

The Kashkan River (KR), located in the west of Iran, is a major source of water supply for residential and agricultural areas as well as livestock. The objective of this study was to assess the spatial and long temporal variations of surface water quality of the KR based on measured chemical ions. The Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) technique was utilized using measurements from 10 sampling stations during a period of 36 years (1974–2009). The measured data included cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), anions (HCO₃ ^?, Cl^?, SO₄ ^2?), pH, and electrical conductivity. Principal component analysis was performed to identify which of the parameters to be included in the CCME WQI calculations were actually correlated and which ones were responsible for most of the variance observed in the water-quality data. In addition, KR water quality was evaluated for its suitability for drinking and irrigation purposes using conventional methods. Last, trend detection in the WQI time series of the KR showed water-quality degradation at all sampling stations, whereas the Jelhool sub-basin more adversely affects the quality of KR water in the watershed. Nonetheless, on average, the water quality of the KR was rated as fair.     

Identification of anthropogenic effects and seasonality on water quality in Daya Bay, South China Sea

Thirteen water quality parameters from 12 monitoring stations were collected to study the effects caused by climate and anthropogenic activities on water quality in 2003 in Daya Bay, South China Sea. The data matrix has been built according to the results, which were analyzed by fuzzy c-mean cluster (FCM) and cluster analysis (CA). This analysis has identified anthropogenic effects and seasonal characters of water quality. The dry and wet seasonality have been demonstrated with FCM and CA. The precipitation and the Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on water quality in Daya Bay. In the spatial pattern, two groups have been classified with FCM and CA. Cluster I consisted of the sites S3, S8, S10 and S11 in the west and north coastal parts of Daya Bay. Cluster I is mainly related to anthropogenic activities such as fish-farming. Cluster II consisted of the rest of the stations in the center, east and south parts of Daya Bay. Cluster II is mainly related to seawater input from South China Sea. Thus, fuzzy c-mean cluster and cluster analysis can be an important tool for the successful characterization of regional-scale water quality.     

Multivariate approach for surface water quality mapping with special reference to nitrate enrichment in Sugadaira,Nagano Prefecture (Japan)

The hydrochemical study of the surface water along with land-use/land-cover study of its catchment area is useful for determining its suitability for support to aquatic ecosystem and agricultural purposes. The surface water quality around the wetland in Sugadaira region, Japan, is being affected both by complex hydrogeochemical processes and by anthropogenic activity, mainly intensive agricultural practices. Statistical analysis was carried out in this study using surface water chemistry data to enable hydrochemical evaluation of the water quality based on the ionic constituents, water types, and factors controlling water quality. Results show that the general trend of various ions was found to be Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ and HCO₃ ⁻ > NO₃ ⁻ > SO₄ ²⁻ > Cl⁻. Spatial distribution of water chemistry shows that enrichment of NO₃ ⁻ has taken place along one side of the wetland that is exposed directly to human settlement and agricultural practices. This study is vital considering that pollution in a wetland indicates that poor health of water resources in the region not only makes the situation alarming but also calls for immediate attention.     

Effects of Land Use and Sample Location on Nitrate‐Stream Flow Hysteresis Descriptors during Storm Events

The U.S. Geological Survey's New Jersey and Iowa Water Science Centers deployed ultraviolet‐visible spectrophotometric sensors at water‐quality monitoring sites on the Passaic and Pompton Rivers at Two Bridges, New Jersey, on Toms River at Toms River, New Jersey, and on the North Raccoon River near Jefferson, Iowa to continuously measure in‐stream nitrate plus nitrite as nitrogen (NO₃ + NO₂) concentrations in conjunction with continuous stream flow measurements. Statistical analysis of NO₃ + NO₂ vs. stream discharge during storm events found statistically significant links between land use types and sampling site with the normalized area and rotational direction of NO₃ + NO₂‐stream discharge (N‐Q) hysteresis patterns. Statistically significant relations were also found between the normalized area of a hysteresis pattern and several flow parameters as well as the normalized area adjusted for rotational direction and minimum NO₃ + NO₂ concentrations. The mean normalized hysteresis area for forested land use was smaller than that of urban and agricultural land uses. The hysteresis rotational direction of the agricultural land use was opposite of that of the urban and undeveloped land uses. An r² of 0.81 for the relation between the minimum normalized NO₃ + NO₂ concentration during a storm vs. the normalized NO₃ + NO₂ concentration at peak flow suggested that dilution was the dominant process controlling NO₃ + NO₂ concentrations over the course of most storm events.     

Pollution and Self-Cleansing of an Urban River in a Developing Country: A Case Study in Dar es Salaam, Tanzania

Pollution and self-purification trends of an urban river namely, Msimbazi River, in Dar es Salaam City, Tanzania, were investigated. Site investigations and water quality analyses were done. The river is polluted in terms of high organic and nutrient concentrations, low dissolved oxygen, and high counts of indicator organisms. Biochemical oxygen demand (BOD₅) concentrations were 27– 340 mg/L. Dissolved oxygen was found to be as low as 0.9 mg O₂/L. Bacteriological pollution increased with distance downstream of the river, a trend attributable to an increase in the catchment of pollution sources, which are on-site sanitation systems. Although the river has an appreciable self-purification capacity, the capacity is strained by persistent pollution overloads. The pollution plight of the river is attributable to its being flanked by expanding human habitats and vibrant industrial, institutional, and socio-economic activities. Provision for pretreatment of discharges into the river is put forward as a remedial measure for the observed pollution. Matching nontechnical and techno-social remedial measures are also recommended. These include sensitization of polluters on merits of environmental protection practices such as cleaner production and strict enforcement of environmental protection laws.     

Impact of industrial air pollutants on some biochemical parameters and yield in wheat and mustard plants

The present study was carried out to determine the impacts of SO₂, NO _x , SPM and RSPM, the most common air pollutants, generated mainly due to industries and vehicles, on some biochemical parameters and yield in wheat and mustard plants during 2006. The concentration of SO₂, NO _x , SPM and RSPM was determined at the polluted sites across the seasons, which ranged between 14.29–18.10, 20.81–22.43, 483.65–500.85 and 160.67–171.18 μg m⁻³, respectively. The wheat and mustard plants grown at polluted sites showed significant reduction in chlorophyll ‘a’, chlorophyll ‘b’, total chlorophyll, carotenoid, ascorbic acid, pH, relative water content and yield. The data were further analyzed using a two way ANOVA. It is concluded that the ambient air pollutants have a potential adverse impact on biochemical parameters, which further leads to a reduction in the yield of wheat and mustard crops.     

我国长江流域中三角区域大气污染物排放特征研究

中三角区域已经是我国第四个国家级城市群,也将成为我国经济增长的"第四极"。在经济发展的同时,更需要以节能减排、资源环境等为重点,以实现经济建设与生态文明"双可持续"的协同发展。本文以二氧化硫、氮氧化物、烟(粉)尘为主要大气污染物,对我国中三角区域大气污染物排放进行了详细的分析,并与京津冀、长三角、珠三角、"三区十群"等进行了多方位比较。结果表明,2013年中三角区域二氧化硫排放量为151.7万t,其中工业二氧化硫排放量为140.1万t;氮氧化物排放量为147.2万t,其中工业氮氧化物排放量为93.6万t;烟(粉)尘排放量为81.8万t,其中工业烟(粉)尘排放量为71.4万t。中三角区域二氧化硫、氮氧化物、烟(粉)尘排放量均位于"四极"的第三。中三角区域二氧化硫、氮氧化物、烟(粉)尘单位GDP排放强度分别为25.03t/亿元、24.29 t/亿元、13.50 t/亿元,分别位于"四极"的第一、第二、第二。同时,本文还从经济发展模式、产业结构调整、煤炭消费方式等方面对我国中三角等经济"四极"提出了相关建议。     

Water quality assessment and meta model development in Melen watershed – Turkey

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the “Quality Required of Surface Water Intended for the Abstraction of Drinking Water” regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH₄⁺, BOD₅, faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO₄^3?, total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters.     

Chemical and isotopic compositions of the Minjiang River, a headwater tributary of the Yangtze River

We describe the anthropogenic impacts on the major dissolved elements (Cl(-), NO(3)(-)-N, SO(4)(2-), and Na(+)) in the water from the Minjiang River (a headwater tributary of the Yangtze River) and upper Yangtze River in relation to increasing human activity. The major element chemistry and hydrogen, oxygen, and sulfur isotopic compositions were investigated. When the Minjiang River flows through the populated Sichuan Basin, the concentrations of Cl(-), NO(3)(-)-N, SO(4)(2-), and Na(+) gradually increase. The increasing SO(4)(2-) in the highly polluted Minjiang River had high delta(34)S values (+6.3 to approximately +13.6 per thousand), implicating the anthropogenic sources of sulfur from air pollutants, domestic wastewater, industrial effluents, and agricultural fertilizers. The water quality of the upper Yangtze River does not worsen after receiving the Minjiang River because the water from the lightly polluted Jinshajiang River contributes most of the total flux in the Yangtze River. However, these rivers deserve attention and further research because the Yangtze River is the most important river in China in terms of water quality.