Optimal charges on river effluent from lumped and distributed sources

We propose a modelling framework for the design of a Pigouvian effluent tax, in an environmental management problem implicating several economic agents located in a river basin. The proposed charging system allows for the agents' geographical position relative to the river's sections, at which environmental standards are to be enforced, and takes into account the possible different market structures within which the agents are operating. In particular, we consider industrial agents competing on an oligopolistic market, and a set of farmers acting as price takers on a large market. A regional authority's goal is to induce agents to some sort of cooperation which would result in the satisfaction of the common environmental constraints. The economic process on one side, and the pollution transport and accumulation on the other, constitute two dynamic processes in two different time scales. As the economic process is much slower than the other process we can neglect the latter's transients and concentrate on the time invariant steady state solutions to the transportation equation. The model thus constructed has some noncooperative game and optimal control problem's features with space being the ‘running’ variable. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modeling the spatial pattern of farmland using GIS and multiple logistic regression: a case study of Maotiao River Basin, Guizhou Province, China

Land use change is an important topic in the field of global environmental change and sustainable development. Land use change modeling has attracted substantial attention because it helps researchers understand the mechanisms of land use change and assists regulatory bodies in formulating relevant policies. Maotiao River Basin is located in the province of Guizhou, China, which has a developed agricultural industry in the karst mountain areas. This paper selected biophysical and social–economic factors as independent variables, and constructed a multiple logistic regression of farmland spatial distribution probability by random sampling. Then, by using GIS technology and integrating the 2000 data, this study predicted the farmland spatial pattern. When the predicted map was compared with the actual farmland map for 2000, we noted that 71% of the simulation is in accordance with the 2000 farmland pattern. The result satisfactorily proves the reasonability and applicability of our model.     

太湖水质氮素质量浓度时空差异特征及影响因素分析

通过对2014—2016年湖体水质中氮素质量浓度分析,结合出入湖总氮浓度、水量、湖体水生生态等影响因素,发现太湖水体中总氮浓度呈现逐年下降的趋势,各监测点位总氮为0.530 mg/L～5.51 mg/L,时空分布不均,差异明显。时间上,总氮浓度表现为春季最高,夏季和秋季最低,且月均值变化曲线呈现出规律的正弦函数波形。空间上,总氮浓度大致表现出由西部湖区向东部湖区递减的趋势,呈现西部湖区﹥北部湖区﹥南部湖区﹥湖心区﹥东部湖区。要改善湖体水质,不仅要切断污染源,而且要加强水生生态功能修复。     

2017年上半年北京市及周边地区空气质量特征分析

依托北京市、廊坊市和保定市高密度的地面空气质量监测、气象要素监测以及PM_2.5化学组分监测和后向轨迹分析等手段，对2017年上半年三地的空气质量进行分析。研究发现：三地中北京市空气质量较好，保定市较差。分污染物来看，保定市SO₂浓度水平明显高于廊坊市和北京市，颗粒物PM₁₀和PM_2.5也呈现保定市最高、北京市最低的规律。从污染物日变化来看，CO、SO₂、NO₂、PM₁₀和PM_2.5呈双峰型分布，O₃呈单峰型分布。从区域整体分布规律来看，PM_2.5和SO₂呈现明显的"南高北低"特征。PM_2.5化学组分分析结果表明：1—4月燃煤对该区域空气质量的影响较大，5—6月机动车排放的影响更为凸显。后向轨迹分析结果表明：在2017年上半年到达北京市的气流中有24%来自于北京市南部，且这些气流多为低空传输，表明区域传输对于北京市空气质量具有一定的影响。     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

Mega-Development Trends in the Amazon: Implications for Global Change

This paper describes four global-change phenomena that are having major impacts on Amazonian forests. The first is accelerating deforestation and logging. Despite recent government initiatives to slow forest loss, deforestation rates in Brazilian Amazonia have increased from 1.1 million ha yr^–1 in the early 1990s, to nearly 1.5 million ha yr^–1 from 1992–1994, and to more than 1.9 million ha yr^–1 from 1995–1998. Deforestation is also occurring rapidly in some other parts of the Amazon Basin, such as in Bolivia and Ecuador, while industrialized logging is increasing dramatically in the Guianas and central Amazonia.The second phenomenon is that patterns of forest loss and fragmentation are rapidly changing. In recent decades, large-scale deforestation has mainly occurred in the southern and eastern portions of the Amazon — in the Brazilian states of Pará, Maranho, Rondônia, Acre, and Mato Grosso, and in northern Bolivia. While rates of forest loss remain very high in these areas, the development of major new highways is providing direct conduits into the heart of the Amazon. If future trends follow past patterns, land-hungry settlers and loggers may largely bisect the forests of the Amazon Basin.The third phenomenon is that climatic variability is interacting with human land uses, creating additional impacts on forest ecosystems. The 1997/98 El Niño drought, for example, led to a major increase in forest burning, with wildfires raging out of control in the northern Amazonian state of Roraima and other locations. Logging operations, which create labyrinths of roads and tracks in forsts, are increasing fuel loads, desiccation and ignition sources in forest interiors. Forest fragmentation also increases fire susceptibility by creating dry, fire-prone forest edges.Finally, recent evidence suggests that intact Amazonian forests are a globally significant carbon sink, quite possibly caused by higher forest growth rates in response to increasing atmospheric CO₂ fertilization. Evidence for a carbon sink comes from long-term forest mensuration plots, from whole-forest studies of carbon flux and from investigations of atmospheric CO₂ and oxygen isotopes. Unfortunately, intact Amazonian forests are rapidly diminishing. Hence, not only is the destruction of these forests a major source of greenhouse gases, but it is reducing their intrinsic capacity to help buffer the rapid anthropogenic rise in CO₂.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

SPATIAL ANALYSIS AND EUTROPHICATION ASSESSMENT FOR CHLOROPHYLL a IN TAIHU LAKE

Spatial structure analysis and kriging analysis have been identified to be useful tools in illustrating the spatial patterns of variables. Taihu Lake is one of the largest fresh water lakes in China, and has suffered serious eutrophication in recent years due to the rapid economic development and growing environmental pollution in the Taihu Catchment. In this paper, spatial structural analysis, kriging interpolation and eutrophication assessment were carried out for chlorophyll a in the lake. Studies show that spherical model could be applied to fit all experimental variograms. Positive nuggets were observed for three directions except NE–SW direction. The variograms show some anisotropy with anisotropic ratio falling within 1.76. The spatial structural patterns of chlorophyll a in the lake were affected by factors such as distribution of pollution sources, water flow and wind. Two-dimensional ordinary block kriging was applied for interpolation process. An eutrophication assessment map was also made based on a water-quality evaluation standard. Results show that the content of chlorophyll a in Taihu Lake was quite high. The whole lake has suffered serious eutrophication. However, the eutrophic situation varied in space. Higher contents of chlorophyll a appeared mainly in the northern part of the lake.     

过氧化聚吡咯/聚乙烯吡咯烷酮修饰碳糊电极测定废水中苯酚

建立了过氧化聚吡咯(OPPy)和聚乙烯吡咯烷酮(PVP)修饰碳糊电极测定废水中苯酚的方法.优化了试验条件,苯酚的氧化峰电流在1.0×10-5 mol/L～1.0×10-3 mol/L之间线性关系良好,检出限为1.0×10-6 mol/L.该电极制作简单,选择性好,测定灵敏度高,精密度与准确度均符合要求.     

MERCURY EMISSION INVENTORY IN ONTARIO

Mercury is released to the environment from various anthropogenic and natural sources. This work is a compilation of mercury emissions from anthropogenic sources in Ontario, Canada. The goal of our study was to identify all sources of mercury, and develop an emission inventory of anthropogenic mercury in Ontario. The result of our investigation revealed that combustion of fossil fuels and emissions from landfill sites are two primary sources of mercury to the atmosphere. Other sources of significance are emissions from waste incinerators, various industrial activities, and cement production. Total mercury emission in Ontario is estimated as 4100 kg per year.