Informe del Grupo de Trabajo sobre estadísticas ambientales de la Conferencia Estadística de las Américas de la CEPAL

Incluye Bibliografía

El Sistema de Cuentas Ambientales y Económicas (SCAE) 2012: fundamentos conceptuales para su implementación

Incluye bibliografía.

Evaluation report of the regional workshop on the measurement of poverty in the Caribbean

1. The member and associate member countries of the Economic Commission for Latin America and the Caribbean/Caribbean Development and Cooperation Committee (ECLAC/CDCC) have committed to pursuing and achieving the Millennium Development Goals, a common set of goals and targets to bring all people up to minimum acceptable standards of human development by 2015. 2. However, in spite of various capacity-building initiatives, Caribbean countries continued to experience difficulties in addressing additional demands of monitoring and measuring progress created by the Millennium Development Goals and other Internationally Agreed Development Goals. Therefore, it was necessary to implement activities to ensure the further building/strengthening of institutional capabilities for generating reliable social, economic and environmental statistics among Caribbean States. 3. The ECLAC project entitled “Strengthening the Capacity of National Statistical Offices in the Caribbean Small Island Developing States to fulfil the Millennium Development Goals and other Internationally Agreed Development Goals” sought to build and strengthen institutional capabilities for generating and compiling reliable social, economic and environmental statistics in the Caribbean subregion, through the provision of technical support, as well as the conduct of training workshops for statisticians and policymakers. 4. Within the objectives of that project, ECLAC Subregional Headquarters for the Caribbean convened a regional training workshop on the measurement of poverty in the Caribbean in Port of Spain, to build the capacity of government officials and other relevant stakeholders. 5. The overall objective of the workshop was to develop and strengthen the national technical capacity of public officials in data processing, systematization and dissemination of poverty indicators and measurement in the Caribbean subregion. The workshop further sought to review and discuss the current approaches to poverty measurement and monitoring in an effort to identify methods to ensure that monitoring and reporting of the Millennium Development Goals were conducted according to internationally agreed upon methodologies. Furthermore, the workshop also intended to review different methods of poverty measurements, including the multidimensional methodology for the measurement of poverty. 6. Participants were introduced to different methods of poverty measurements and other aggregation proposals which would enable countries to better measure progress towards Goal 1 on poverty, report on it and apply evidence-based approaches to national policymaking and planning.

Emisiones de gases de efecto invernadero y mitigación en el sector residuos: la economía del cambio climático en la Argentina

En este estudio se analizaron las emisiones de gases de efecto invernadero (GEI) y su mitigación en el sector residuos. Se examinó la producción de residuos sólidos urbanos y aguas residuales domésticas e industriales, observándose una relación significativa entre ésta y el Producto Interno Bruto. Las emisiones de GEI en el sector se calcularon mediante el método de descomposición de primer orden en las ciudades con datos de actividad sobre los residuos y en las restantes con el método por defecto.

Quantifying simulator discrepancy in discrete-time dynamical simulators

When making predictions with complex simulators it can be important to quantify the various sources of uncertainty. Errors in the structural specification of the simulator, for example due to missing processes or incorrect mathematical specification, can be a major source of uncertainty, but are often ignored. We introduce a methodology for inferring the discrepancy between the simulator and the system in discrete-time dynamical simulators. We assume a structural form for the discrepancy function, and show how to infer the maximum-likelihood parameter estimates using a particle filter embedded within a Monte Carlo expectation maximization (MCEM) algorithm. We illustrate the method on a conceptual rainfall-runoff simulator (logSPM) used to model the Abercrombie catchment in Australia. We assess the simulator and discrepancy model on the basis of their predictive performance using proper scoring rules. This article has supplementary material online. © 2011 International Biometric Society.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Impact of product-related environmental regulations in Asia : descriptive statistics from a survey of firms in Penang, Malaysia

This paper summarizes the main results of a unique firm survey conducted in Penang, Malaysia in 2012 on product-related environmental regulations. The results show that firms receiving foreign-direct investment have adapted well to regulations but faced more rejections. Several research questions are addressed and examined by using the survey data. Major findings are as follows. First, adaptation involves changes in input procurement and market diversification, which potentially changes the structure of supply chains. Second, belonging to global supply chains is a key factor in compliance, but this requires firms to meet tougher customer requirements. Third, there is much room for government policy to play a role in assisting firms.

Impact of product-related environmental regulations in Asia : descriptive statistics from a survey of firms in Vietnam

This paper summarizes the main results of a unique firm survey conducted in Vietnam in 2011 on product-related environmental regulations (PRERs). The results of this survey are compared with the results of a corresponding survey of firms in Penang, Malaysia (Michida, et al. 2014b). The major findings are as follows. First, adaptation to PRERs involves changes in input procurement and results in market diversification, which potentially alters the structure of supply chains. This finding is consistent with the Malaysian survey result. Second, connections to global supply chains are key to compliance, but this requires firms to meet more stringent customer requirements. Third, government policy can play an important role in assisting firms to comply with PRERs.

Exploratory spatial analysis of social and environmental factors associated with the incidence of Ross River Virus in Brisbane, Australia

We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.

Preliminary spatiotemporal analysis of the association between socio-environmental factors and suicide

Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.

Socio-environmental factors and suicide in Queensland, Australia

Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.

Environmental reporting and its relation to corporate environmental performance

This study examines how both the level and the nature of environmental information voluntarily disclosed by Australian firms relate to their underlying environmental performance. Disclosure is scored using an index developed by Clarkson et al. (2008) based on Global Reporting Initiative (GRI) Guidelines and the environmental performance measure is based on emission data available from the National Pollutant Inventory (NPI). The sample consists of 51 firms that reported to the NPI in both 2002 and 2006. The findings are as follows. First, descriptive statistics indicate that while there was modest improvement in disclosure between 2002 and 2006, the highest disclosure score obtained was just slightly in excess of 50% of the maximum available based on the GRI Guidelines. Second, the results consistently indicate that not only do firms with a higher pollution propensity disclose more environmental information; they also rely on disclosures that the GRI views as inherently more objective and verifiable. Taken together, these results suggest that concerns regarding the reliability of voluntary environmental disclosures in the Australian context remain valid and thereby potentially signal a need for both enhanced mandatory reporting requirements and improved enforcement. In this regard, our study also informs regulatory policy on mandatory disclosures of environmental performance.

Statistical and scientometric analysis of international research in geographical and environmental education

Certain statistic and scientometric features of articles published in the journal “International Research in Geographical and Environmental Education” are examined in this paper, for the period 1992-2009, by applying nonparametric statistics and Shannon’s entropy (diversity) formula. The main findings of this analysis are: a) after 2004 the research priorities of researchers in geographical and environmental education seem to have changed, b) “teacher education” has been the most recurrent theme throughout these 18 years, followed by “values & attitudes” and “inquiry & problem solving” c) the themes “GIS” and “Sustainability” were the most “stable” throughout the 18 years, meaning that they maintained their ranks as publication priorities more than other themes, d) citations of IRGEE increase annually, e) the average thematic diversity of articles published during the period 1992-2009 is 82.7% of the maximum thematic diversity (very high), meaning that the Journal has the capacity to attract a wide readership for the 10 themes it has successfully covered throughout the 18 years of its publication.

What it means to be green : an examination of early stage environmental and sustainability focused firms

This paper examines ‘green’ entrepreneurial nascent and young firms in Australia. Findings of interest in this paper include: • Green entrepreneurs are more likely to be highly educated and have an extended depth of experience within their industry and are more likely to have started a business prior to their current venture. • Green entrepreneurs exhibit increased levels of innovation, with an increased focus on new & high technology, R&D and the development of proprietary technology. • Green entrepreneurs are most likely to be based upon a product rather than a service and have a higher emphasis upon growth when compared with non-green entrepreneurs. • Green entrepreneurial firms tend to have a longer venture creation process and draw financial resources from a larger number of sources and rely more upon equity as a means of financing their venture.