Spatial assessment of carbon stocks of living vegetation at the national level in Lao PDR

The international mechanism for Reducing Greenhouse Gas Emissions from Deforestation and Forest Degradation (REDD) supposedly offers new opportunities for combining climate mitigation, conservation of the environment, and socio-economic development for development countries. In Laos REDD is abundantly promoted by the government and development agencies as a potential option for rural development. Yet, basic information for carbon management is missing: to date no knowledge is available at the national level on the quantities of carbon stored in the Lao landscapes. In this study we present an approach for spatial assessment of vegetation-based carbon stocks. We used Google Earth, Landsat and MODIS satellite imagery and refined the official national land cover data to assess carbon stocks. Our study showed that more than half (52%) of carbon stock of Laos is stored in natural forests, but that 70% of this stock is located outside of national protected areas. On the basis of two carbon-centered land use scenarios we calculated that between 30 and 40 million tons of carbon could be accumulated in shifting cultivation areas; this is less than 3% of the existing total stock. Our study suggests that the main focus of REDD in Laos should be on the conservation of existing carbon stocks, giving highest priority to the prevention of deforestation outside of national protected areas.

LiDAR remote sensing applied to forest resources assessment

Disponer de informaci��n precisa y actualizada de inventario forestal es una pieza clave para mejorar la gesti��n forestal sostenible y para proponer y evaluar pol��ticas de conservaci��n de bosques que permitan la reducci��n de emisiones de carbono debidas a la deforestaci��n y degradaci��n forestal (REDD). En este sentido, la tecnolog��a LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en ��reas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el n��mero de pies, el volumen de madera, la altura dominante, el di��metro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicaci��n de los denominados m��todos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y caracter��sticas de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (informaci��n proveniente de vuelo nacionales e informaci��n capturada de forma espec��fica). Como consecuencia de lo anterior, se profundiza en la generaci��n de inventarios forestales continuos con LiDAR en grandes ��reas. Los m��todos de masa se basan en la b��squeda de relaciones estad��sticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartograf��a continua de inventario forestal. El r��pido desarrollo de esta tecnolog��a en los ��ltimos a��os ha llevado a muchos pa��ses a implantar programas nacionales de captura de informaci��n LiDAR aerotransportada. Estos vuelos nacionales no est��n pensados ni dise��ados para fines forestales por lo que es necesaria la evaluaci��n de la validez de esta informaci��n LiDAR para la descripci��n de la estructura del bosque y la medici��n de variables forestales. Esta informaci��n podr��a suponer una dr��stica reducci��n de costes en la generaci��n de informaci��n continua de alta resoluci��n de inventario forestal. En el cap��tulo 2 se eval��a la estimaci��n de variables forestales a partir de la informaci��n LiDAR capturada en el marco del Plan Nacional de Ortofotograf��a A��rea (PNOA-LiDAR) en Espa��a. Para ello se compara un vuelo espec��fico dise��ado para inventario forestal con la informaci��n de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra c��mo el ��ngulo de escaneo, la pendiente y orientaci��n del terreno afectan de forma estad��sticamente significativa, aunque con peque��as diferencias, a la estimaci��n de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas result�� m��s afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimaci��n de la biomasa con ambas bases de datos no present�� diferencias estad��sticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimaci��n de biomasa entre un vuelo espec��fico y el vuelo nacional podr��n superar el 4% en ��reas abruptas, con ��ngulos de escaneo altos y cuando la pendiente de la ladera no est�� orientada hacia la l��nea de escaneo. En el cap��tulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la informaci��n disponible (vuelos LiDAR nacionales de baja densidad de puntos, im��genes satelitales Landsat y parcelas permanentes del inventario forestal nacional espa��ol). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resoluci��n en grandes superficies. Los errores obtenidos en la fase de ajuste y de validaci��n de los modelos de ��rea basim��trica y volumen son similares a los registrados por otros autores (usando un vuelo espec��fico y parcelas de campo espec��ficas). Se observan errores mayores en la variable n��mero de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodolog��a de parcelas de radio variable en esta variable. En los cap��tulos 4 y 5 se eval��an los m��todos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volc��n Po��s (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del ��rea de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es t��cnica o econ��micamente posible y se combina una cobertura incompleta de LiDAR con im��genes Landsat e informaci��n auxiliar para la estimaci��n de biomasa y carbono (capitulo 5). En el cap��tulo 4 se valida un modelo LiDAR general de estimaci��n de biomasa a��rea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma espec��fica para el ��rea de estudio. Ambos modelos est��n basados en la variable altura media de copas (TCH por sus siglas en ingl��s) derivada del modelo digital LiDAR de altura de la vegetaci��n. Los resultados en el ��rea de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos espec��ficos y que la biomasa a��rea puede ser estimada en una nueva zona midiendo en campo ��nicamente la variable ��rea basim��trica (BA). Para mejorar la aplicaci��n de esta metodolog��a es necesario definir en futuros trabajos procedimientos adecuados de medici��n de la variable ��rea basim��trica en campo (localizaci��n, tama��o y forma de las parcelas de campo). La relaci��n entre la altura media de copas del LiDAR y el ��rea basim��trica (Coeficiente de Stock) obtenida en el ��rea de estudio var��a localmente. Por tanto es necesario contar con m��s informaci��n de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificaci��n pueden reducir los errores en la estimaci��n de biomasa y carbono en bosques tropicales. En el cap��tulo 5 se concluye que la combinaci��n de una muestra sistem��tica de informaci��n LiDAR con una cobertura completa de imagen satelital de moderada resoluci��n (e informaci��n auxiliar) es una alternativa efectiva para la realizaci��n de inventarios continuos en bosques tropicales. Esta metodolog��a permite estimar altura de la vegetaci��n, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realizaci��n de un gran volumen de trabajo de campo es econ��mica o/y t��cnicamente inviable. Las alternativas examinadas para la predicci��n de biomasa a partir de im��genes Landsat muestran una ligera disminuci��n del coeficiente de determinaci��n y un peque��o aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetaci��n, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del ��rea de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15��. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

RED vs. REDD: Biofuel Policy vs. Forest Conservation. Factor Markets Working Document No. 41, May 2013

This paper assesses the complex interplay between global Renewable Energy Directives (RED) and the United Nations programme to Reduce Emissions from Deforestation and forest Degradation (REDD). We examine the interaction of the two policies using a scenario approach with a recursive-dynamic global Computable General Equilibrium model. The consequences of a global biofuel directive on worldwide land use, agricultural production, international trade flows, food prices and food security out to 2030 are evaluated with and without a strict global REDD policy. We address a key methodological challenge of how to model the supply of land in the face of restrictions over its availability, as arises under the REDD policy. The paper introduces a flexible land supply function, which allows for large changes in the total potential land availability for agriculture. Our results show that whilst both RED and REDD are designed to reduce emissions, they have opposing impacts on land use. RED policies are found to extend land use whereas the REDD policy leads to an overall reduction in land use and intensification of agriculture. Strict REDD policies to protect forest and woodland lead to higher land prices in all regions. World food prices are slightly higher overall with some significant regional increases, notably in Southern Africa and Indonesia, leading to reductions in food security in these countries. This said, real food prices in 2030 are still lower than the 2010 level, even with the RED and REDD policies in place. Overall this suggests that RED and REDD are feasible from a worldwide perspective, although the results show that there are some regional problems that need to be resolved. The results show that countries directly affected by forest and woodland protection would be the most economically vulnerable when the REDD policy is implemented. The introduction of REDD policies reduces global trade in agricultural products and moves some developing countries to a net importing position for agricultural products. This suggests that the protection of forests and woodlands in these regions reverses their comparative advantage as they move from being land-abundant to land-scarce regions. The full REDD policy setting, however, foresees providing compensation to these countries to cover their economic losses.

Sizing reserves within a landscape: the roles of villagers' reactions and the ecological-socioeconomic setting

Traditionally, siting and sizing decisions for parks and reserves reflected ecological characteristics but typically failed to consider ecological costs created from displaced resource collection, welfare costs on nearby rural people, and enforcement costs. Using a spatial game-theoretic model that incorporates the interaction of socioeconomic and ecological settings, we show how incorporating more recent mandates that include rural welfare and surrounding landscapes can result in very different optimal sizing decisions. The model informs our discussion of recent forest management in Tanzania, reserve sizing and siting decisions, estimating reserve effectiveness, and determining patterns of avoided forest degradation in Reduced Emissions from Deforestation and Forest Degradation programs.

Reduction of greenhouse gas emissions from UK hotels in 2030

The feasibility of halving greenhousegasemissions from hotels by 2030 has been studied as part of the Carbon Vision Buildings Programme. The aim of that programme was to study ways of reducing emissions from the existing stock because it will be responsible for the majority of building emissions over the next few decades. The work was carried out using detailed computer simulation using the ESP-r tool. Two hotels were studied, one older and converted and the other newer and purpose-built, with the aim of representing the most common UKhotel types. The effects were studied of interventions expected to be available in 2030 including fabric improvements, HVAC changes, lighting and appliance improvements and renewable energy generation. The main finding was that it is technically feasible to reduce emissions by 50% without compromising guest comfort. Ranking of the interventions was problematical for several reasons including interdependence and the impacts on boiler sizing of large reductions in the heating load

The Mutagenic Potential Caused by the Emissions from Combustion of Crude Glycerin and Diesel Fuel

Conselho Nacional de Desenvolvimento Cient��fico e Tecnol��gico (CNPq)

Protecting Tropical Forests through Public Procurement of Emission Reductions

The rate of destruction of tropical forests continues to accelerate at an alarming rate contributing to an important fraction of overall greenhouse gas emissions. In recent years, much hope has been vested in the emerging REDD+ framework under the UN Framework Convention on Climate Change (UNFCCC), which aims at creating an international incentive system to reduce emissions from deforestation and forest degradation. This paper argues that in the absence of an international consensus on the design of results-based payments, ���bottom-up��� initiatives should take the lead and explore new avenues. It suggests that a call for tender for REDD+ credits might both assist in leveraging private investments and spending scarce public funds in a cost-efficient manner. The paper discusses the pros and cons of results-based approaches, provides an overview of the goals and principles that govern public procurement and discusses their relevance for the purchase of REDD+ credits, in particular within the ambit of the European Union.

Resource use and greenhouse gas emissions from grain-finishing beef cattle in seven Australian feedlots: a life cycle assessment

Grain finishing of cattle has become increasingly common in Australia over the past 30 years. However, interest in the associated environmental impacts and resource use is increasing and requires detailed analysis. In this study we conducted a life cycle assessment (LCA) to investigate impacts of the grain-finishing stage for cattle in seven feedlots in eastern Australia, with a particular focus on the feedlot stage, including the impacts from producing the ration, feedlot operations, transport, and livestock emissions while cattle are in the feedlot (gate-to-gate). The functional unit was 1 kg of liveweight gain (LWG) for the feedlot stage and results are included for the full supply chain (cradle-to-gate), reported per kilogram of liveweight (LW) at the point of slaughter. Three classes of cattle produced for different markets were studied: short-fed domestic market (55���80 days on feed), mid-fed export (108���164 days on feed) and long-fed export (>300 days on feed). In the feedlot stage, mean fresh water consumption was found to vary from 171.9 to 672.6 L/kg LWG and mean stress-weighted water use ranged from 100.9 to 193.2 water stress index eq. L/kg LWG. Irrigation contributed 57���91% of total fresh water consumption with differences mainly related to the availability of irrigation water near the feedlot and the use of irrigated feed inputs in rations. Mean fossil energy demand ranged from 16.5 to 34.2 MJ lower heating values/kg LWG and arable land occupation from 18.7 to 40.5 m2/kg LWG in the feedlot stage. Mean greenhouse gas (GHG) emissions in the feedlot stage ranged from 4.6 to 9.5 kg CO2-e/kg LWG (excluding land use and direct land-use change emissions). Emissions were dominated by enteric methane and contributions from the production, transport and milling of feed inputs. Linear regression analysis showed that the feed conversion ratio was able to explain >86% of the variation in GHG intensity and energy demand. The feedlot stage contributed between 26% and 44% of total slaughter weight for the classes of cattle fed, whereas the contribution of this phase to resource use varied from 4% to 96% showing impacts from the finishing phase varied considerably, compared with the breeding and backgrounding. GHG emissions and total land occupation per kilogram of LWG during the grain finishing phase were lower than emissions from breeding and backgrounding, resulting in lower life-time emissions for grain-finished cattle compared with grass finishing.

La cooperaci��n internacional para el desarrollo como herramienta de pol��tica exterior japonesa en ��frica Subsahariana

El presente caso de estudio tiene como objetivo explicar el rol de la cooperaci��n internacional para el desarrollo en Tanzania, Mozambique, Nigeria para la consolidaci��n del liderazgo pol��tico internacional de Jap��n. El inter��s de realizar esta investigaci��n es la ampliaci��n del conocimiento sobre el uso del poder blando, para alcanzar los objetivos de pol��tica exterior japonesa. Por eso, se llevara a cabo una revisi��n bibliogr��fica para el an��lisis de documentos oficiales y art��culos acad��micos para la consolidaci��n de informaci��n. A partir de ello, se pretende demostrar que la cooperaci��n al desarrollo es una herramienta de pol��tica exterior japonesa para consolidarse como l��der, en la medida en que el uso de herramientas propias de la cooperaci��n y el presupuesto destinada a la ejecuci��n de ��stas tienen incidencia en los votos de estos Estados africanos para las iniciativas japonesas en las Naciones Unidas.

Spatial Variability of CO2 Emissions from Newly Exposed Paraglacial Soils at a Glacier Retreat Zone on King George Island, Maritime Antarctica

Conselho Nacional de Desenvolvimento Cient��fico e Tecnol��gico (CNPq)

Do Global CO2 Emissions from Fossil-Fuel Consumption Exhibit Long Memory? A Fractional Integration Analysis

In this article we use an autoregressive fractionally integrated moving average approach to measure the degree of fractional integration of aggregate world CO2 emissions and its five components ��� coal, oil, gas, cement, and gas flaring. We find that all variables are stationary and mean reverting, but exhibit long-term memory. Our results suggest that both coal and oil combustion emissions have the weakest degree of long-range dependence, while emissions from gas and gas flaring have the strongest. With evidence of long memory, we conclude that transitory policy shocks are likely to have long-lasting effects, but not permanent effects. Accordingly, permanent effects on CO2 emissions require a more permanent policy stance. In this context, if one were to rely only on testing for stationarity and non-stationarity, one would likely conclude in favour of non-stationarity, and therefore that even transitory policy shocks

Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

Modeling the spatial and temporal heterogeneity of deforestation-driven carbon emissions: the INPE-EM framework applied to the Brazilian Amazon

We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

The policy relevance of wear emissions from road transport, now and in the future : an international workshop report and consensus statement

Road transport emissions are a major contributor to ambient particulate matter concentrations and have been associated with adverse health effects. Therefore, these emissions are targeted through increasingly stringent European emission standards. These policies succeed in reducing exhaust emissions, but do not address "nonexhaust" emissions from brake wear, tire wear, road wear, and suspension in air of road dust. Is this a problem? To what extent do nonexhaust emissions contribute to ambient concentrations of PM10 or PM2.5? In the near future, wear emissions may dominate the remaining traffic-related PM10 emissions in Europe, mostly due to the steep decrease in PM exhaust emissions. This underlines the need to determine the relevance of the wear emissions as a contribution to the existing ambient PM concentrations, and the need to assess the health risks related to wear particles, which has not yet received much attention. During a workshop in 2011, available knowledge was reported and evaluated so as to draw conclusions on the relevance of traffic-related wear emissions for air quality policy development. On the basis of available evidence, which is briefly presented in this paper, it was concluded that nonexhaust emissions and in particular suspension in air of road dust are major contributors to exceedances at street locations of the PM10 air quality standards in various European cities. Furthermore, wear-related PM emissions that contain high concentrations of metals may (despite their limited contribution to the mass of nonexhaust emissions) cause significant health risks for the population, especially those living near intensely trafficked locations. To quantify the existing health risks, targeted research is required on wear emissions, their dispersion in urban areas, population exposure, and its effects on health. Such information will be crucial for environmental policymakers as an input for discussions on the need to develop control strategies.

To what extent are CO2 emissions from intra-urban shopping trips by cars affected by drivers��� travel behaviour and store location?

Transportation is seen as one of the major sources of CO2 pollutants nowadays. The impact of increased transport in retailing should not be underestimated. Most previous studies have focused on transportation and underlying trips, in general, while very few studies have addressed the specific affects that, for instance, intra-city shopping trips generate. Furthermore, most of the existing methods used to estimate emission are based on macro-data designed to generate national or regional inventory projections. There is a lack of studies using micro-data based methods that are able to distinguish between driver behaviour and the locational effects induced by shopping trips, which is an important precondition for energy efficient urban planning. The aim of this study is to implement a micro-data method to estimate and compare CO2 emission induced by intra-urban car travelling to a retail destination of durable goods (DG), and non-durable goods (NDG). We estimate the emissions from aspects of travel behaviour and store location. The study is conducted by means of a case study in the city of Borl��nge, where GPS tracking data on intra-urban car travel is collected from 250 households. We find that a behavioural change during a trip towards a CO2 optimal travelling by car has the potential to decrease emission to 36% (DG), and to 25% (NDG) of the emissions induced by car-travelling shopping trips today. There is also a potential of reducing CO2 emissions induced by intra-urban shopping trips due to poor location by 54%, and if the consumer selected the closest of 8 existing stores, the CO2 emissions would be reduced by 37% of the current emission induced by NDG shopping trips.