Cattle vaccination records question the impact of recent zero-deforestation agreements in the Amazon

Regional Environmental Change - In the late 2000s, slaughterhouses across the Amazon entered into a series of agreements designed to reduce the environmental impact of the local cattle sector. In...     

Development Potentials and Policy Options of Biomass in China

Biomass, one of the most important renewable energies, is playing and will continue to play an important role in the future energy structure of the world. This article aims to analyze the position and role, assess the resource availability, discuss the geographic distribution, market scale and industry development, and present the policy options of biomass in China. The resource availability and geographical distribution of biomass byproducts are assessed in terms of crop residues, manure, forest and wood biomass byproducts, municipal waste and wastewater. The position of biomass use for power generation is just next to hydropower among types of renewable energy in China. The potential quantity of all biomass byproducts energy in 2004 is 3511 Mtce (Mtce is the abbreviation of million tons of coal equivalents and 1 Mtce is equal to10⁶ tce.), while the acquirable quantity is 460 Mtce. Biomass energy plays a critical role in rural regions of China. The geographical distribution and quantity of biomass byproducts resources depends mainly on the relationship between ecological zones and climate conditions. Our estimation shows that the total quantity of crop residues, manure, forest and wood biomass byproducts, municipal waste and wastewater resources are 728, 3926, 2175, 155 and 48240 Mt (million tons), respectively. Crop residues come mainly from the provinces of Henan, Shandong, Heilongjiang, Jilin and Sichuan. All manure is mainly located in the provinces of Henan, Shandong, Sichuan, Hebei and Hunan. Forest and wood biomass byproducts are mainly produced in the provinces or autonomous regions of Tibet, Sichuan, Yunnan, Heilongjiang and Inner Mongolia, while most of municipal waste mainly comes from Guangdong, Shandong, Heilongjiang, Hubei and Jiangsu. Most of wastewater is largely discharged from advanced provinces like Guangdong, Jiangsu, Zhejiang, Shandong and Henan. Biomass byproducts’ energy distribution also varies from province to province in China. Based on the analysis of the market scale and industry development, the article argues that China’s biomass energy industry is still at a very early stage of development and that Feed-in Tariffs (FIT) might be the best policy option for China to promote its development of biomass energy. A successful enforcement of FIT in China needs some policy combination of special capital subsidies, R&D funding, tax incentives and pricing.     

Modeling phosphorus transport in an agricultural watershed using the WEPP model

The Water Erosion Prediction Project (WEPP) model has been tested for its ability to predict soil erosion, runoff, and sediment delivery over a wide range of conditions and scales for both hillslopes and watersheds. Since its release in 1995, there has been considerable interest in adding a chemical transport element to it. Total phosphorus (TP) loss at the watershed outlet was simulated as the product of TP in the soil, amount of sediment at the watershed outlet, and an enrichment ratio (ER) factor. WEPP can be coupled with a simple algorithm to simulate phosphorus transport bound to sediment at the watershed outlet. The objective of this work was to incorporate and test the ability of WEPP in estimatingTP loss with sediment at the small watershed scale. Two approaches were examined. One approach (P-EER) estimated ER according to an empirical relationship; the other approach used the ER calculated by WEPP (P-WER).The data used for model performance test were obtained from two side-by-side watersheds monitored between 1976 and 1980. The watershed sizes were 5.05 and 6.37 ha, and each was in a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. Measured and simulated results were compared for the period April to October in each year. There was no statistical difference between the mean measured and simulated TP loss. The Nash-Sutcliffe coefficient was 0.80 and 0.78 for the P-EER and P-WER methods, respectively. It was critical for both methods that WEPP adequately represent the biggest sediment yield events because sediment is the main driver for TP loss so that the model can adequately simulate TP losses bound to sediment. The P-WER method is recommended because it does not require use of empirical parameters to estimate TP loss at the watershed outlet.     

High efficiencies in the electrochemical oxidation of an anthraquinonic dye with conductive-diamond anodes

Oxidation of anthraquinonic dye Acid Blue 62 by electrolysis with conductive-diamond electrodes is studied in this work. COD, TOC, and color have been selected to monitor the degradation of the molecule as a function of several operating inputs (current density, pH, temperature, and NaCl concentration). Results show that the electrochemical oxidation of this model of large molecules follows a first order kinetics in all the conditions assessed, and it does not depend on the pH and temperature. The occurrence of chloride ions in wastewaters increases the rate of color and COD removal as a consequence of the mediated oxidation promoted by the chlorinated oxidizing species. However, chloride occurrence does not have an influence on the mineralization rate. First-order kinetic-constants for color depletion (attack to chromophores groups), oxidation (COD removal), and mineralization (TOC removal) were found to depend on the current density and to increase significantly with its value. A single model was proposed to explain these changes in terms of the mediated oxidation processes. Rate of mineralization remained very close to that expected for a purely mass transfer-controlled process. This was explained assuming that mediated oxidation does not have a significant influence on the mineralization in spite it has some effect on intermediate oxidation stages. The efficiency of the oxidation was found to depend mainly on the concentration of COD being negligible the effect of the other inputs assessed except for the occurrence of chloride ions. Opposite, the efficiency of mineralization depends on concentration of TOC and current density and it did not depend on the chloride occurrence. This observation was found to have an important influence on the power required to remove a given percentage of the initial TOC or COD. To decrease COD efficiently, the occurrence of chloride in the solution is very important, while to remove TOC efficiently, it is more important to work at low current densities and chloride effect is negligible. Energy consumption could be decreased by folds using the proper conditions.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Air Quality in Selected Megacities

Abstract

About half of the world's population now lives in urban areas because of the opportunity for a better quality of life. Many of these urban centers are expanding rapidly, leading to the growth of megacities, which are often defined as metropolitan areas with populations exceeding 10 million inhabitants. These concentrations of people and activity are exerting increasing stress on the natural environment, with impacts at urban, regional and global levels. In recent decades, air pollution has become one of the most important problems of megacities. Initially, the main air pollutants of concern were sulfur compounds, which were generated mostly by burning coal. Today, photochemical smog—induced primarily from traffic, but also from industrial activities, power generation, and solvents—has become the main source of concern for air quality, while sulfur is still a major problem in many cities of the developing world. Air pollution has serious impacts on public health, causes urban and regional haze, and has the potential to contribute significantly to global climate change. Yet, with appropriate planning megacities can efficiently address their air quality problems through measures such as application of new emission control technologies and development of mass transit systems.

This review is focused on nine urban centers, chosen as case studies to assess air quality from distinct perspectives: from cities in the industrialized nations to cities in the developing world. This review considers not only megacities, but also urban centers with somewhat smaller populations, for while each city—its problems, resources, and outlook—is unique, the need for a holistic approach to complex environmental problems is the same. There is no single strategy to reduce air pollution in megacities; a mix of policy measures will be needed to improve air quality. Experience shows that strong political will coupled with public dialogue is essential to effectively implement the regulations required to address air quality.     

Modeling Inorganic Aerosols and Their Response to Changes in Precursor Concentration in Mexico City

Abstract

Based on data from the 1997 Investigación sobre Materia Particulada y Deterioro Atmosférico-Aerosol and Visibility Evaluation Research (IMADA-EVER) campaign and the inorganic aerosol model ISORROPIA, the response of inorganic aerosols to changes in precursor concentrations was calculated. The aerosol behavior is dominated by the abundance of ammonia and thus, changes in ammonia concentration are expected to have a small effect on particle concentrations. Changes in sulfate and nitrate are expected to lead to proportional reductions in inorganic fine particulate matter (PM_2.5). Comparing the predictions of ISORROPIA with the observations, the lowest bias and error are achieved when the aerosols are assumed to be in the efflorescence branch. Including crustal species reduces the bias and error for nitrate but does not improve overall model performance. The estimated response of inorganic PM_2.5 to changes in precursor concentrations is affected by the inclusion of crustal species in some cases, although average responses are comparable with and without crustal species. Observed concentrations of particle chloride suggest that gas phase concentrations of hydrogen chloride may not be negligible, and future measurement campaigns should include observations to test this hypothesis. Our ability to model aerosol behavior in Mexico City and, thus, design control strategies, is constrained primarily by a lack of observations of gas phase precursors. Future campaigns should focus in particular on better understanding the temporal and spatial distribution of ammonia concentrations. In addition, gas phase observations of nitric acid are needed, and a measure of particle water content will allow stable versus metastable aerosol behavior to be distinguished.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Use of hematological and plasma biochemical parameters to assess the chronic effects of a fungicide propiconazole on a freshwater teleost

Blood is an indicator of physiological condition of an animal. Therefore, the chronic effects of propiconazole, a triazole fungicide present in aquatic environment, on hematology of rainbow trout were investigated in this study. Fish were exposed at various concentrations of PCZ (0.2, 50 and 500 μg L(-1)) for 7, 20 and 30 d. Multiple biomarkers were measured, including hematological indices (hemoglobin concentration, red blood cells count, hematocrit, leukocyte count, mean erythrocyte hemoglobin, mean erythrocyte volume and mean color concentration) and plasma biochemical parameters (ammonia, glucose, total proteins, creatine kinase, lactate dehydrogenase, alanine aminotransferase and aspartate aminotransferase). Through principal component analysis and integrated biomarker response assessment, influence extent induced by PCZ-stress of each test group was distinguished. Additional, all parameters measured in this study displayed different dependent patterns to PCZ concentrations and exposure time by two-way ANOVA. The results of this study indicate that chronic exposure of PCZ has altered multiple physiological indices in fish hematology and CK activity may be an early biomarker of PCZ toxicity; however, before these parameters are used as special biomarkers for monitoring residual PCZ in aquatic environment, more detailed experiments in laboratory need to be performed in the future.