A Global Model Tracking Water, Nitrogen, and Land Inputs and Virtual Transfers from Industrialized Meat Production and Trade

Rising populations and incomes throughout the world have boosted meat demand by over 75% in the last 20years, intensifying pressures on production systems and the natural resources to which they are linked. As a growing proportion of global meat production is traded, the environmental impacts of production become increasingly separated from where the meat is consumed. In this paper, we quantify the use of three important resources associated with industrial livestock production and trade—water, land, and nitrogen—using a country-specific model that combines trade, agronomic, biogeochemical, and hydrological data. Our model focuses on pigs and chickens, as these animals are raised predominantly in intensive systems using concentrated, compound feeds. The results describe the geographical patterns of environmental resource use due to meat production, trade, and consumption. We show that US feed, animal, and meat destined for export require almost as much nitrogen and land, and 20% more water, than products destined for domestic consumption. Model results also demonstrate that among various production factors, improvements in crop yields and animal feed conversion efficiencies result in the most significant reductions in environmental harm. By explicitly tracking the externalities of meat production, we hope to bolster suppliers’ accountability and provide better information to meat consumers.

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

Hydrogeochemical data as a tool for exploration and mapping: a case study from part of Afikpo Basin southeastern Nigeria

Fourteen (14) characters from six (6) water samples collected from springs, ponds, and streams located in Lower Cretaceous sedimentary area of Afikpo Basin have been analyzed. These include pH, turbidity, conductivity, total dissolved solid, hardness, Fe²⁺, Ca²⁺, Mg²⁺, K⁺, NO₃ ^?, Cl^?, SO₄ ^2?, and Na⁺. These sediments, which are Turonian and Coniacian in age, are subdivided into two by a basic rock dyke. Results of the analyses show clearly that the Turonian sediments, intruded by dolerite, have net Fe²⁺, HCO₃ ^?, Ca²⁺, Mg²⁺, Mn²⁺, Cl^?, and SO₄ ^2? concentration while those from the younger Coniacian sediment have net higher amounts of K⁺, Na⁺, and Mn²⁺. The overriding mafic minerals in the basic intrusive rock possibly led to higher leaching into ground water system near it. On the other hand, the presence of feldsparthic to kaolinitic sands of the younger Coniacian units led to higher K⁺ and Na⁺ matter in the water from these zones. The formations dip away from the older sediments. Concentrations of these characters are within acceptable drinking water standards by World Health Organization but noticeable anomalous zones for Fe²⁺, Mg²⁺, and Ca²⁺ are zones of basic rock suites. Areas with greater Na⁺ and K⁺ are traceable to sandy units. It is thus concluded that more analysis of surface, subsurface, and pond water samples can be utilized for minerals search and geological mapping. At this stage, it forms a veritable reconnaissance tool.     

Analysis of the air pollution climate at a background site in the Po valley

The Po valley in northern Italy is renowned for its high air pollutant concentrations. Measurements of air pollutants from a background site in Modena, a town of 200 thousand inhabitants within the Po valley, are analysed. These comprise hourly data for CO, NO, NO(2), NO(x), and O(3), and daily gravimetric equivalent data for PM(10) from 1998-2010. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and auto-correlation and cross-correlation functions. CO, NO and NO(2) exhibit a strongly traffic-related pattern, with daily peaks at morning and evening rush hour and lower concentrations over the weekend. Ozone shows an annual cycle with a peak in July due to local production; notwithstanding the diurnal cycle dominated by titration by nitrogen oxide, the decreasing long term trend in NO concentration did not affect the long term trend in O(3), whose mean concentration remained steady over the sampling period. PM(10) shows a strong seasonality with higher concentration in winter and lower concentration in summer and spring. Both PM(10) and ozone show a marked weekly cycle in summer and winter respectively. Regressions of PM(10) upon NO(x) show a consistently greater intercept in winter, representing higher secondary PM(10) in the cooler months of the year. There is a seasonal pattern in primary PM(10) to NO(x) ratios, with lower values in winter and higher values in summer, but the reasons are unclear.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.     

Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.     

Calculating losses of crops in Denmark caused by high ozone levels

In order to help guide air pollution legislation at the European level, harmful air pollution effects on agriculture crops and the consequent economic implications for policy have been studied for more than a decade. Ozone has been labeled as the most serious of the damaging air pollutants to agriculture, where growth rates and consequently yields are dramatically reduced. Quantifying the effects has formed a key factor in policymaking. Based on the widely held view that AOT40 (Accumulated exposure Over Threshold of 40 ppb) is a good indicator of ozone-induced damage, the Danish Eulerian Model (DEM) was used to compute reduced agriculture yields on a 50 km×50 km grid over Europe. In one set of scenarios, a ten year meteorological time series was combined with realistic emission inventories. In another, various idealized emission reduction scenarios are applied to the same meteorological time series. The results show substantial inter-annual variability in economic losses, due in most part to meteorological conditions which varied much more substantially than the emissions during the same period. It is further shown that, taking all uncertainties into account, estimates of ozone-induced economic losses require that a long meteorological record is included in the analysis, for statistical significance to be improved to acceptable levels for use in policy analysis. In this study, calculations were made for Europe as a whole, though this paper presents results relevant for Denmark.     

Micromorphology and chemistry of airborne particles in Brussels during agriculture working periods in surrounding region

The main objective of our research was to compare the airborne particle micromorphology and chemistry in the Brussels environment during agriculture working periods in the surrounding farming region. We used specific methods and instrumentation that are adapted to the climate peculiarities of the Brussels region, the period of investigations (12 months) and the proposed objectives. For the agricultural works we defined the following six periods: before sowing, sowing, after sowing, before harvest, harvest and after harvest. The results indicate a possible temporal correlation between agricultural work periods and airborne particle concentration, micromorphology and chemistry in the Brabant-Brussels region. For wheat and corn plant-growth periods, the average particle size, defined as the area obtained by a planar projection of the particulate, showed important variations in time. For sugar beet and endive, the average area size variations are less important. The roughness and sphericity parameters for the growth periods of the four different plants also showed significant differences. Many of the larger particulates (> 10 microm) are aggregates of even finer particles coated with many still finer ones. The airborne particle chemistry averages (atomic percentage At%), showed that three constituents (Si, S and Fe) dominate all the samples (except for particles 3-10 microm in size, which contain a relatively large percentage of Al). Applying similar investigation methods to study the correlations between airborne particle dynamics in urban zones and the agriculture working periods in their surrounding regions could be of interest to better understand the complexity of the PM problematic.     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.     

Geochemical assessment of metal concentrations in sediment core of Korangi Creek along Karachi Coast, Pakistan

Sediment core from Korangi Creek, one of the polluted coastal locations along the Karachi Coast Pakistan, was collected to trace the history of marine pollution and to determine the impact of industrial activity in the area. Down core variation of metals such as Ca, K, Mg, Al, S, Ti, V, Cr, Mn, Fe, Ni, Cu and Zn was studied in the 72.0 cm core. Nuclear analytical techniques, proton induced X-rays emission (PIXE), was employed to ascertain the chemical composition in sediment core. Grain size analysis and sediment composition of cored samples indicated that Korangi creek sediments are clayey in nature. Correlation matrix revealed a strong association of Ni, Cu, Cr and Zn with Fe and Mn. To infer anthropogenic input, enrichment factor (EF), degree of contamination and pollution load index were calculated. EF showed severe enrichment in surface sediment for Ni, Cu, Cr and Zn, indicating increased industrial effluents discharge in recent years. The study suggests that heavy metal discharge in the area should be regulated. If the present trend of enrichment is allowed to continue unabated, it is most likely that the local food web complexes in the creek might be at highest risk.