British Journal of Environment and Climate Change最新文献

{"title":"A Preliminary Estimation on Carbon Footprint of Raw Water from the Reservoirs for Domestic Use in Taiwan","authors":"Y. H. Wang, C. Su, W. Huang, Y. Kuang, Y. D. Huang, W. L. Wu, C. Chu, Y. J. Chung","doi":"10.9734/BJECC/2014/8573","DOIUrl":"https://doi.org/10.9734/BJECC/2014/8573","url":null,"abstract":"This study aims to evaluate the carbon footprint of raw water from reservoirs for domestic use in Taiwan. It also provides a preliminary measure and reference database for greenhouse gas (GHG) emission of reservoir systems in Taiwan. Four reservoirs, Feitsui (F.T.) and Liyutan (L.Y.T.) in subtropical zone and Nanhua (N.H.) and Tsengwen (T.W.) in tropical zone, were selected as the cases to be examined for carbon footprint inventory, including the GHG emission from the water body and from human activities. Carbon footprint inventory followed PAS 2050 (2011 Specification for the assessment of the life cycle greenhouse gas emissions of goods and services). GHG emission from water body followed the instruction of UNESCO guidelines. The boundary of this inventory covers the water intake works, impoundment region, the dam, the affiliated hydroelectricity power plant, the administration center and other facilities. In this study, the floating chambers with gas chromatography (GC) were chosen to measure the GHG flux from the water body. For the emission of CH4 and N2O from the water body, there are no significantly difference between the fluxes during the daytime and nighttime. For Original Research Article British Journal of Environment & Climate Change, 4(1): 45-65, 2014 46 carbon dioxide, the instantaneous flux during the nighttime is higher than the daytime flux. The two reservoirs in tropical zone emit more CO2e from the water body than those in subtropical zone. Summarizing the direct and indirect GHG emission, for the four reservoirs, the annual emission quantities ranged from 653 ton of CO2e to 23,146 ton of CO2e. The carbon footprint of water supply for domestic use ranged from 0.002 kg CO2e/m to 0.028 kg CO2e/m. Roughly speaking, the total GHG emission quantity of the 24 main reservoirs in Taiwan was estimated to be around 121,800 ton of CO2e with the total yield of 4.35 billion m of water annually using the highest carbon footprint 0.028 kg CO2e/m.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116574916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of extreme floods on groundwater quality (in Pakistan).","authors":"T. Saeed, Haleema Attaullah","doi":"10.9734/BJECC/2014/4105","DOIUrl":"https://doi.org/10.9734/BJECC/2014/4105","url":null,"abstract":"Study of long and short-term impact of hydro-meteorologically induced extreme flood on groundwater from well is a baby science, yet to grow and groom. This article focuses on the environmental impacts of the worst Pakistani floods on water quality of affected areas, Charsadda and Nowshera districts in Khyber Pakhtunkhwa province which experienced a disastrous flood in its record due to torrential monsoon rains in late July 2010. For this purpose, consuming water products from 10 main sources (tube wells), 10 intermediate points in water supply distribution system and 10 consumers’ ends in 30 selected sites of flood affected areas were collected and analyzed for 12 key factors. Most of the parameters with respect to the standard limits of WHO guidelines indicated contamination in all samples that are directly available from tube wells as well as the one supplied through damaged pipe distribution system. This result becomes more fatal in the presence of microbial contamination and makes water risky for domestic consumption. A concrete policy addressing post-flood environmental effects on life and human health should be devised and strictly followed. Individual cases must be assessed from a basinwide perspective in order to make sure that environmental concerns are judiciously and properly represented in flood planning and risk management decisions.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129967234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term precipitation trends in eastern Slovakia.","authors":"M. Zeleňáková","doi":"10.9734/BJECC/2014/10655","DOIUrl":"https://doi.org/10.9734/BJECC/2014/10655","url":null,"abstract":"The objective of this study was to investigate precipitation trends in climatic stations in eastern Slovakia. We investigated 20 climatic stations in Slovakia. The studied period was from 1981 to 2010. Monthly precipitation trends were detected by nonparametric MannKendall statistical test. Positive trends of annual as well as monthly precipitation were found in the analyzed rainfall gauging stations in eastern Slovakia. March was observed to have the highest decreasing trends. All other months displayed mostly increasing trends. In quartile research mostly the summer period shows positive trends in precipitation. In conclusion, Slovakia has an increasing trend of precipitation time series.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114616492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Toward a Sustainable and Resilient City – Development of Adaptation Measures to Climate Change","authors":"C. Kao","doi":"10.9734/BJECC/2014/9230","DOIUrl":"https://doi.org/10.9734/BJECC/2014/9230","url":null,"abstract":"The earth is undergoing a warming process and we are facing an increasing possibility that extreme natural disasters are on the rise because of global warming as well as climate change. The increased temperature resulted from the enhanced greenhouse effects has been found to be an important factor, which significantly affects the earth’s hydrological cycles. Furthermore, the increases in temperature and changes in rainfall pattern occur around the globe.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128329786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate Impact on Freshwater Biodiversity: General Patterns in Extreme Environments of North-Eastern Siberia (Russia)","authors":"S. Barinova, V. Gabyshev, O. Gabysheva","doi":"10.9734/BJECC/2014/9530","DOIUrl":"https://doi.org/10.9734/BJECC/2014/9530","url":null,"abstract":"Aims: The aims of the current study are to reveal the response of high latitude riverine planktonic algal communities in northeastern Siberia to extreme climatic conditions of its habitats. Study Design: We implemented diverse statistical methods, which represent some new approaches in freshwater algal diversity analysis. Place and Duration of Study: Institute of Evolution, University of Haifa, Israel, Institute for Biological Problems of Cryolithozone SB RAS, Russia, between June 2008 and Original Research Article British Journal of Environment & Climate Change, 4(4): 423-443, 2014 424 January 2014. Methodology: We collected 800 samples of phytoplankton from 400 sites of 12 northeastern Siberian rivers in gradients of climatic and chemical variables that we analyzed. New indices Geo-associated and Dynamic Habitat Index were included in this analysis. Statistical methods for comparative floristic analyses were used for calculating the similarity of algal communities among the sampling stations. Multiple regression stepwise statistical analysis on phytoplankton including chemical and climatic variables data was performed. Species diversity in algal communities and their environmental variables relationships were calculated. Results: As a result, 1283 species (1637 taxa of species and infraspecies) from six taxonomic divisions were identified in phytoplankton communities. Species richness as a whole increased to the north. Abundance and biomass were highly correlated. Two types of phytoplankton communities were identified: a southern community with increasing diatoms and a northern group with decreasing diatoms to the north. Diatoms prevailed but were replaced by green algae in high mountains or by green and Chrysophyta algae and Cyanobacteria in the Arctic. We revealed major variables that considered stimulating or stress factors with helps of statistical prorgams. Conclusion: Statistical analyses of phytoplankton in 12 large rivers revealed an increase in species richness to the north with community structure changing under stimulation of air temperature, ice-free periods, humidity, and trophic variables were stimulants and water transparency and speed flow were considered stress factors.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133165884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Drought Severity and Duration Using Copulas in Anuradhapura, Sri Lanka","authors":"E. Ekanayake, Kanthi Perera","doi":"10.9734/BJECC/2014/14482","DOIUrl":"https://doi.org/10.9734/BJECC/2014/14482","url":null,"abstract":"Anuradhapura district is one of the largest agricultural crop production areas in Sri Lanka. But it is often affected by droughts and droughts caused severe damage for agricultural industry. Thus it is very important to identify the drought characteristics (drought duration and drought severity) and their joint probability distribution to minimize the adverse effects of droughts. Drought characteristics were defined using 3 - month standard precipitation index (SPI). It is calculated using monthly rainfall da ta from 1951 to 2007 in Anuradhapura. Occurrences of 46 drought events were indentified using the calculated SPI. Since dependency nature of the drought variables, copula based joint distribution was used to calculate the joint distribution. The joint dis tribution could be obtained by combining the marginal distributions using copula. Five copulas were examined and compared to find the best fitted copula to represent the joint distribution . The best marginal distributions were identified as the gamma distr ibutions for drought durations and drought severity using AIC, BIC and Kolmogorov - Smirnov test. Frank copula was","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125925640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Climate Change, Poverty and Macroeconomic Policies on Agricultural Trade Performance in Nigeria","authors":"A. Onoja, A. Achike","doi":"10.9734/BJECC/2014/8575","DOIUrl":"https://doi.org/10.9734/BJECC/2014/8575","url":null,"abstract":"Aims: This study ascertained the joint influences of climate factors, poverty and macroeconomic environment on agricultural export performance in Nigeria. Study Design: The study is a survey based on time series data. Place and Duration of Study: Secondary data covering 32 years (1978-2009) obtained from Central Bank of Nigeria’s Annual Report and Statistical Bulletin and National Bureau of Statistics were used for the survey. Methodology: The sample size was 32 (years) based on data availability. Data analysis was conducted using bound testing approach of co-integration advanced by Pesaran et al. [25] otherwise known as Autoregressive Distributed Lag (ARDL).model. Test for unit roots in the series were done at their levels and first differences using Augmented Dickey Fuller and Philips Perron tests before applying the ARDL model. Results: Preliminary results from the ARDL model indicated that climate variability (variations in mean annual rainfall), gross fixed capital formation (proxy for wealth accumulated in the economy) and macroeconomic variables including interest rate and volume of domestic credit advanced to the private sector significantly influenced the performance level of agricultural export. However, on the long-run, macroeconomic factors (interest rate and credit to the private sector) and gross fixed capital of the economy (with p values of 0.01, 0.07 and 0.03 respectively were the most significant","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127948956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Special issue on climate change impacts and mitigation on water quality and ecological health in aquatic systems.","authors":"X. Fang","doi":"10.9734/BJECC/2014/15400","DOIUrl":"https://doi.org/10.9734/BJECC/2014/15400","url":null,"abstract":"The increase of carbon dioxide (CO2) and other greenhouse gases in the atmosphere is projected to cause climate change and global warming. The understanding of climate change impacts on water quality in aquatic systems (lakes, streams, reservoirs, and estuaries) is fundamental in providing better environmental strategies and mitigation methods to protect ecological health of aquatic systems. Water quality is a critical issue due to its direct influence on public health, biological integrity of natural resources, and the economy. The climate change leads to possible changes in local and global weather conditions, such as higher air temperatures and variable precipitation (both intensity and magnitude). Climate conditions affect hydrology in watersheds and then water quality conditions in aquatic systems. To make the projection on future climate, various General Circulation Models (GCMs) of the earth’s atmosphere have been developed. These GCM models simulate time series of climate parameters that can be used to create future climate scenarios for hydrological and water quality studies in watersheds and aquatic systems.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129024868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Topographic effects on vegetation biomass in semiarid mixed grassland under climate change using AVHRR NDVI data.","authors":"Liu Zhaoqin, Guo Xulin","doi":"10.9734/BJECC/2014/11146","DOIUrl":"https://doi.org/10.9734/BJECC/2014/11146","url":null,"abstract":"The topography effects on vegetation biomass under climate change impact have been ignored in prairie regions as it is not as significant as in mountain areas. This paper aims to investigate the topographic effects on vegetation biomass under climate change in semiarid Canadian mixed grass prairie. The study site is Grasslands National Park (GNP) and the study period is from 1985 to 2007. Data used include dry green biomass data sampled from June to July of 2003 to 2005, 10-day Advanced Very High Resolution Radiometer (AVHRR) 1km Normalized Difference Vegetation Index (NDVI) composites of 1985 to 2007, and Global Digital Elevation Model derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER GDEM) data with 90 m resolution. To achieve the objective, the applicability of AVHRR NDVI data being a proxy of vegetation biomass was investigated. Then, the range and standard deviation (SD) of each individual vegetation patch in both valley and upland grasslands were calculated. In addition, the variation trend of valley and upland vegetation was analyzed respectively using the Mann-Kendall (M-K) test and the Sen’s slope. The results indicate that the interannual variation of vegetation biomass at GNP can be fairly well represented by AVHRR 1 km NDVI data. Although some patches in valley grassland have similar NDVI range and SD values as those in upland grassland, the others have much smaller range and SD Short Research Article British Journal of Environment & Climate Change, 4(2): 229-242, 2014 230 values than the highest range (0.154) and SD (0.045) of upland grassland. The M-K test and Sen’s slope analyses indicate that NDVI had an increase trend with a larger slope (0.0005) in upland and a smaller slope (0.0002) in valley grassland. It is concluded that climatic variation has more effects on upland grassland than valley grassland in GNP. Topography effects in prairie regions should not be ignored.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124399771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate change and the risk of Highly Pathogenic Avian Influenza outbreaks in birds.","authors":"Jianhong E. Mu, B. McCarl, Ximing Wu, M. Ward","doi":"10.9734/BJECC/2014/8888","DOIUrl":"https://doi.org/10.9734/BJECC/2014/8888","url":null,"abstract":"In this paper, we examine the association between climate change and outbreak probability of Highly Pathogenic Avian Influenza A virus (HPAI H5N1) in birds. Climate change is a potential factor for the recent spread of H5N1 outbreaks because it can directly alter the conditions involved in persistence of the virus and disease transmission. Also it can contribute indirectly by changing wild bird migration patterns. Econometric analyses using a dynamic Probit model over monthly data from January 2004 to December 2008 found that a 1% rise in winter total precipitation increases the risk of HPAI H5N1 outbreaks by 0.26%. Spring mean temperature was also found to have positive and significant impacts. Our findings are robust across different model specifications and under out-of-sample tests. Using historical data we find the realized climate change of the last 20 years partly explains the recent expansion in outbreaks. Under future climate change projections, we find that countries having higher projected spring temperature or more winter precipitation or both, such as Japan and Romania, will have large increases in outbreak probabilities. This suggests that climate change may play an even greater role in Original Research Article British Journal of Environment & Climate Change, 4(2): 166-185, 2014 167 the future, although magnitudes will vary across countries and climate projections. From a policy perspective, future climate conditions may give rise to a need for different disease control and prevention strategies.","PeriodicalId":373103,"journal":{"name":"British Journal of Environment and Climate Change","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124237263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}