Uncertainties in the current knowledge of some atmospheric trace gases associated with U.S. agriculture: a review

Approximately 80 different crop species are grown in the United States in widely differing geographic areas, climatic and edaphic conditions, and management practices. Although the majority of cultivated acreage in the United States is planted with only about 10 primary crops, uncertainties associated with trace gas emissions arise from: (1) limited data availability, (2) inaccurate estimates because of large temporal and spatial variability in trace gas composition and magnitude of trace gas emissions from agricultural activities, (3) differing characteristics of pollutant emissions from highly dispersed animal feed-lots, and (4) limited understanding of the emissions of semi-volatile organic compounds (SVOCs) associated with agriculture. Although emission issues are of concern, so also is atmospheric deposition to cropping systems, including wet and dry nitrogen, minerals, and organic compounds. These can have feedback effects on trace gas emissions. Overall, the many gaps in our understanding of these aspects of agricultural systems deserve serious attention.     

Uncertainties in the Current Knowledge of Some Atmospheric Trace Gases Associated with U.S. Agriculture: A Review

Abstract

Approximately 80 different crop species are grown in the United States in widely differing geographic areas, climatic and edaphic conditions, and management practices. Although the majority of cultivated acreage in the United States is planted with only about 10 primary crops, uncertainties associated with trace gas emissions arise from: (1) limited data availability, (2) inaccurate estimates because of large temporal and spatial variability in trace gas composition and magnitude of trace gas emissions from agricultural activities, (3) differing characteristics of pollutant emissions from highly dispersed animal feed-lots, and (4) limited understanding of the emissions of semi-volatile organic compounds (SVOCs) associated with agriculture. Although emission issues are of concern, so also is atmospheric deposition to cropping systems, including wet and dry nitrogen, minerals, and organic compounds. These can have feedback effects on trace gas emissions. Overall, the many gaps in our understanding of these aspects of agricultural systems deserve serious attention.     

The measurement of water scarcity: Defining a meaningful indicator

Metrics of water scarcity and stress have evolved over the last three decades from simple threshold indicators to holistic measures characterising human environments and freshwater sustainability. Metrics commonly estimate renewable freshwater resources using mean annual river runoff, which masks hydrological variability, and quantify subjectively socio-economic conditions characterising adaptive capacity. There is a marked absence of research evaluating whether these metrics of water scarcity are meaningful. We argue that measurement of water scarcity (1) be redefined physically in terms of the freshwater storage required to address imbalances in intra- and inter-annual fluxes of freshwater supply and demand; (2) abandons subjective quantifications of human environments and (3) be used to inform participatory decision-making processes that explore a wide range of options for addressing freshwater storage requirements beyond dams that include use of renewable groundwater, soil water and trading in virtual water. Further, we outline a conceptual framework redefining water scarcity in terms of freshwater storage.     

Virtual phosphorus ore requirement of Japanese economy

Phosphorus is indispensable for agricultural production. Hence, the consumption of imported food indirectly implies the import of phosphorus resources. The global consumption of agricultural products depends on a small number of ore-producing countries. For sustainable management of phosphorus resources, the global supply and demand network should be clarified. In this study, we propose the virtual phosphorus ore requirement as a new indicator of the direct and indirect phosphorus requirements for our society. The virtual phosphorus ore requirement indicates the direct and indirect demands for phosphorus ore transformed into agricultural products and fertilizer. In this study, the virtual phosphorus ore requirement was evaluated for the Japanese economy in 2005. Importantly, the results show that our society requires twice as much phosphorus ore as the domestic demand for fertilizer production. The phosphorus contained in “eaten” agricultural products was only 12% of virtual phosphorus ore requirement.     

Determining temporal and spatial variations in ozone air quality

Unless the change in emissions is substantial, the resulting improvement in ozone air quality can be easily masked by the meteorological variability. Therefore, the meteorological and chemical signals must be separated in examining ozone trends. In this paper, we discuss the use of the Kolmogorov-Zurbenko filter in evaluating the temporal and spatial variations in ozone air quality utilizing ozone concentration data from several monitoring locations in the northeastern United States. The results indicate a downward trend in the ozone concentrations during the period 1983-1992 at most locations in the northeastern United States. The results also reveal that ozone is a regional-scale problem in the Northeast.     

深圳笔架山水厂优化节水的实验研究

针对目前我国城镇需水量大、原水费用高的问题,大多数水厂通过降低自用水量的方式节约水资源。经过在笔架山水厂进行的生产性实验,优化耗水工艺的运行条件,挖潜了该水厂的节水空间,自用水量降低。优化后,全处理系统可节约水资源76.83万m3/a,耗水率由原来的2.08%下降到1.49%,同时水厂的经济效益也得到了显著提高,优化后可在原来的基础上节约运行成本近60万元/a。     

污水灌溉的研究进展

科学合理地利用污水灌溉,可以缓解日益紧张的水资源供需矛盾,充分利用污水的水肥资源,提高经济效益,保护生态环境.总结了国内外污水灌溉的发展概况和研究进展,包括污水灌溉对土壤理化特性的影响、对植物生长的影响以及对地下水的影响,并针对中国污水灌溉存在的问题,探讨了污水灌溉技术的发展方向.     

Current status of agricultural and rural non-point source Pollution assessment in China

Estimates of non-point source (NPS) contribution to total water pollution in China range up to 81% for nitrogen and to 93% for phosphorus. We believe these values are too high, reflecting (a) misuse of estimation techniques that were developed in America under very different conditions and (b) lack of specificity on what is included as NPS. We compare primary methods used for NPS estimation in China with their use in America. Two observations are especially notable: empirical research is limited and does not provide an adequate basis for calibrating models nor for deriving export coefficients; the Chinese agricultural situation is so different than that of the United States that empirical data produced in America, as a basis for applying estimation techniques to rural NPS in China, often do not apply. We propose a set of national research and policy initiatives for future NPS research in China.     

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.     

Sustaining food self-sufficiency of a nation: The case of Sri Lankan rice production and related water and fertilizer demands

Rising human demand and climatic variability have created greater uncertainty regarding global food trade and its effects on the food security of nations. To reduce reliance on imported food, many countries have focused on increasing their domestic food production in recent years. With clear goals for the complete self-sufficiency of rice production, Sri Lanka provides an ideal case study for examining the projected growth in domestic rice supply, how this compares to future national demand, and what the associated impacts from water and fertilizer demands may be. Using national rice statistics and estimates of intensification, this study finds that improvements in rice production can feed 25.3 million Sri Lankans (compared to a projected population of 23.8 million people) by 2050. However, to achieve this growth, consumptive water use and nitrogen fertilizer application may need to increase by as much as 69 and 23 %, respectively. This assessment demonstrates that targets for maintaining self-sufficiency should better incorporate avenues for improving resource use efficiency.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0720-2) contains supplementary material, which is available to authorized users.     

Future Impacts of Distributed Power Generation on Ambient Ozone and Particulate Matter Concentrations in the San Joaquin Valley of California

ABSTRACT

Distributed power generation—electricity generation that is produced by many small stationary power generators distributed throughout an urban air basin—has the potential to supply a significant portion of electricity in future years. As a result, distributed generation may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality. However, the use of combined heating and power with distributed generation may reduce the energy consumption for space heating and air conditioning, resulting in a net decrease of pollutant and greenhouse gas emissions. This work used a systematic approach based on land-use geographical information system data to determine the spatial and temporal distribution of distributed generation emissions in the San Joaquin Valley Air Basin of California and simulated the potential air quality impacts using state-of-the-art three-dimensional computer models. The evaluation of the potential market penetration of distributed generation focuses on the year 2023. In general, the air quality impacts of distributed generation were found to be small due to the restrictive 2007 California Air Resources Board air emission standards applied to all distributed generation units and due to the use of combined heating and power. Results suggest that if distributed generation units were allowed to emit at the current Best Available Control Technology standards (which are less restrictive than the 2007 California Air Resources Board standards), air quality impacts of distributed generation could compromise compliance with the federal 8-hr average ozone standard in the region.

IMPLICATIONS The San Joaquin Valley is a fast growing region that demands increasing power generation to sustain the economic development, and at the same time it is one of the worst polluted areas in the United States. Hence, the region demands alternatives that minimize the air quality impacts of power generation. This paper addresses the air quality impacts of distributed generation of power, an alternative to central power generation that can potentially reduce greenhouse gas and pollutant emissions throughout the United States.     

Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Abstract

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM_2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM_2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM_2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.     

Spatial and temporal variability of water repellency in a sandy soil contaminated with tar oil and heavy metals

Water repellency can induce preferential flow and thus affect water flow and contaminant transport at hazardous waste sites. Since the spatial patterns of water repellency are mostly unknown, it is problematic to use numerical transport models to predict leachate composition. In this study, the spatial variability of soil water repellency was studied at an industrial site contaminated with tar oil, chromium, copper and arsenic. The persistence of water repellency was assessed by the water drop penetration time (WDPT), and the degree of water repellency was quantified by the ethanol percentage (EP) test. Measurements were made at the soil surface along 3.5-12.1 m long transects at different times between March and October 2002. The spatial variability of WDPT, EP, water content, and organic matter content was quantified by variogram analyses. Both the persistence and the degree of water repellency varied seasonally, with the highest water repellency during the summer months. The correlation lengths of WDPT values ranged between 16 and 406 cm, whereas EP values showed no spatial correlation. For field-moist samples, a critical soil water threshold, below which water repellency prevails, was estimated to be 2.5-4%. For oven dry samples, the WDPT values were dependent on the water content prior to drying. The wide range of correlation lengths and the temporal dynamics of spatial repellency patterns suggest that simulations of solute leaching must consider the spatial and temporal variability of soil hydrophobic properties.     

Assessment of water quality in the Alqueva Reservoir (Portugal) using bioassays

Background, aim, and scope  

Alqueva Reservoir is the biggest artificial freshwater reservoir in Europe and is an important water supply for human and agricultural consumption in the Alentejo region (Portugal). Pollution can impair environmental and human health status, and to assure water quality and ecological balance, it is crucial to frequently monitor water supplies. In this study, we used an ecotoxicological test battery to identify the potential toxicity of water from this reservoir.     

Characterizing Long-Term Land Use/Cover Change in the United States from 1850 to 2000 Using a Nonlinear Bi-analytical Model

We relate the historical (1850–2000) spatial and temporal changes in cropland cover in the conterminous United States to several socio-economic and biophysical determinants using an eco-region based spatial framework. Results show population density as a major determinant during the nineteenth century, and biophysical suitability as the major determinant during the twentieth century. We further examine the role of technological innovations, socio-economic and socio-ecological feedbacks that have either sustained or altered the cropland trajectories in different eco-regions. The cropland trajectories for each of the 84 level-III eco-regions were analyzed using a nonlinear bi-analytical model. In the Eastern United States, low biophysically suitable eco-regions, e.g., New England, have shown continual decline in the cropland after reaching peak levels. The cropland trajectories in high biophysically suitable regions, e.g., Corn Belt, have stabilized after reaching peak levels. In the Western United States, low-intensity crop cover (<10 %) is sustained with irrigation support. A slower rate of land conversion was found in the industrial period. Significant effect of Conservation Reserve Program on planted crop area is found in last two decades (1990–2010).     

太湖流域小型水源性湖泊氮、磷时空分布及营养状态评价

2009年11月至2010年10月,对太湖流域小型水源性湖泊20个采样点水体的TN、TP、NO3--N、NH4+-N、NO2--N以及PO43-等水质因子进行测定分析,讨论了氮、磷时空分布特征,并评价其富营养化程度。结果表明,TN、TP年均值分别为1.50、0.05mg/L;TN、TP的季节性变化规律具有一定差异,TN浓度为冬、春季高于夏、秋季,而TP浓度为2009年11月至2010年3月高于其他月份。由于受入湖河流的影响,TN、TP的空间分布格局较为相似,均表现为西南部高于东北部、入湖口分别高于湖中心和出湖口。NO3--N年均值为0.68mg/L,浓度变化趋势呈双峰型(2010年3、9月为峰值),基本同TN的变化趋势一致,空间分布表现为入湖口分别低于湖中心和出湖口(除冬季外),显示水体硝化过程对硝酸盐的贡献。NH4+-N年均值为0.23mg/L,从2010年4月开始浓度逐渐升高,到2010年7月达到全年最高值,其浓度空间分布特征表现为入、出湖口均高于湖中心(除秋季外)。NO2--N和PO43-的年均值都较低,均为0.01mg/L(以P计),时空差异不明显。根据CARLSON提出的营养状态指数法计算分析可知,该湖泊冬、春季处于中营养状态,夏、秋季营养状态略高,且磷是全年初级生产力的限制因子。     

Process Based Modelling of Phosphorus Losses from Arable Land

Improved understanding of temporal and spatial Phosphorus (P) discharge variations is needed for improved modelling and prioritisation of abatement strategies that take into account local conditions . This study is aimed at developing modelling of agricultural Phosphorus losses with improved spatial and temporal resolution, and to compare the accuracy of a detailed process-based model with a rainfall-runoff coefficient-based model. The process-based SWAT model (Soil and Water Assessment Tool) was implemented for five river basins in central Sweden, and results compared with the rainfall-runoff coefficient-based model WATSHMAN (Watershed Management System) for one of these river basins. Parameter settings and attribute values were adapted to Scandinavian soil conditions, crops and management practices. Model performance regarding flow dynamics was overall satisfactory. Comparable results were achieved at several scales. The modelled P load was of high accuracy for the days when monitoring data were available for validation, generally once a month. Modelled monthly P load did not fit as well with averaged monthly monitoring load values, mainly since monthly monitoring often partly or entirely misses the peak flows. The comparison of SWAT and WATSHMAN gave slightly better results for the process-based model (SWAT). Better spatial resolution for input data such as Soil-P content and agricultural management practices will be required to reach modelling results that enable identification of measures adapted to local conditions.     

A new approach to data evaluation in the non-target screening of organic trace substances in water analysis

Non-target screening via high performance liquid chromatography-mass spectrometry (HPLC-MS) has gained increasingly in importance for monitoring organic trace substances in water resources targeted for the production of drinking water. In this article a new approach for evaluating the data from non-target HPLC-MS screening in water is introduced and its advantages are demonstrated using the supply of drinking water as an example. The crucial difference between this and other approaches is the comparison of samples based on compounds (features) determined by their full scan data. In so doing, we take advantage of the temporal, spatial, or process-based relationships among the samples by applying the set operators, UNION, INTERSECT, and COMPLEMENT to the features of each sample. This approach regards all compounds, detectable by the used analytical method. That is the fundamental meaning of non-target screening, which includes all analytical information from the applied technique for further data evaluation. In the given example, in just one step, all detected features (1729) of a landfill leachate sample could be examined for their relevant influences on water purification respectively drinking water. This study shows that 1721 out of 1729 features were not relevant for the water purification. Only eight features could be determined in the untreated water and three of them were found in the final drinking water after ozonation. In so doing, it was possible to identify 1-adamantylamine as contamination of the landfill in the drinking water at a concentration in the range of 20 ng L⁻¹. To support the identification of relevant compounds and their transformation products, the DAIOS database (Database-Assisted Identification of Organic Substances) was used. This database concept includes some functions such as product ion search to increase the efficiency of the database query after the screening. To identify related transformation products the database function “transformation tree” was used.     

Health risk assessment of heavy metals in Cyprinus carpio (Cyprinidae) from the upper Mekong River

The purposes of this research are to quantify the concentration of heavy metals (Zn, Cu, As, Pb, Cd, and Hg) in the water and fish tissues of common carp (Cyprinus carpio) in the upper Mekong River and to thereby elucidate the potential dietary health risks from fish consumption of local residents. Surface water and fish tissues (gill, muscle, liver, and intestine) from four representative sample areas (influence by a cascade of four dams) along the river were analyzed for heavy metal concentrations. Results revealed that the levels of heavy metals in fish were tissue-dependent. The highest Cu and As levels were found in the liver; the highest Zn and Pb levels occurred in the intestine, and the highest Hg level was found in the muscle. The total target hazard quotient (THQ) value for residents is > 1 for long-term fish consumption, and local residents are, therefore, exposed to a significant health risk. Results from the current study provide an overall understanding of the spatial and tissue distribution of heavy metals in water and fish body along the upper Mekong River under the influence of cascade dams and highlight the potential health risk of As for the local residents of long-term fish consumption.

     

An assessment of the emissions inventory processing systems EMS-2001 and SMOKE in grid-based air quality models

In the United States, emission processing models such as Emissions Modeling System-2001 (EMS-2001), Emissions Preprocessor System-Version 2.5 (EPS2.5), and the Sparse Matrix Operator Kernel Emissions (SMOKE) model are currently being used to generate gridded, hourly, speciated emission inputs for urban and regional-scale photochemical models from aggregated pollutant inventories. In this study, two models, EMS-2001 and SMOKE, were applied with their default internal data sets to process a common inventory database for a high ozone (O3) episode over the eastern United States using the Carbon Bond IV (CB4) chemical speciation mechanism. A comparison of the emissions processed by these systems shows differences in all three of the major processing steps performed by the two models (i.e., in temporal allocation, spatial allocation, and chemical speciation). Results from a simulation with a photochemical model using these two sets of emissions indicate differences on the order of +/- 20 ppb in the predicted 1-hr daily maximum O3 concentrations. It is therefore critical to develop and implement more common and synchronized temporal, spatial, and speciation cross-reference systems such that the processes within each emissions model converge toward reasonably similar results. This would also help to increase confidence in the validity of photochemical grid model results by reducing one aspect of modeling uncertainty.