Assessment of recovery of European surface waters from acidification 1970-2000: An introduction to the Special Issue

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Carbon in global waste and wastewater flows – its potential as energy source under alternative future waste management regimes

This study provides a quantification of the maximum energy that can be generated from global waste and wastewater sectors in the timeframe to 2050, as well as of the potential limitations introduced by different future waste and wastewater management regimes. Results show that considerable amounts of carbon are currently stored in waste materials without being recovered for recycling or made available for energy generation. Future levels of energy recovery when maintaining current states of waste and wastewater management systems are contrasted with those that can be attained under a circular system identified here as a system with successful implementation of food and plastic waste reduction policies, maximum recycling rates of all different types of waste streams, and once the recycling capacity is exhausted, incineration of remaining materials to produce energy. Moreover, biogas is assumed to be produced from anaerobic codigestion of food and garden wastes, animal manure, and anaerobically treated wastewater. Finally, we explore the limits for energy generation from waste and wastewater sources should the efficiency of energy recovery be pushed further through development of existing technology. We find that global implementation of such an ideal system could increase the relative contribution of waste and wastewater sources to global energy demand from 2% to 9% by 2040, corresponding to a maximum energy potential of 64 EJ per year. This would however require widespread adoption of policies and infrastructure that stimulate and allow for large-scale waste prevention and separation, as well as highly advanced treatment processes. Giving priority to such efforts would enable circularity of the waste-energy system

Ozone concentrations and damage for realistic future European climate and air quality scenarios

Ground level ozone poses a significant threat to human health from air pollution in the European Union. While anthropogenic emissions of precursor substances (NOx, NMVOC, CH4) are regulated by EU air quality legislation and will decrease further in the future, the emissions of biogenic NMVOC (mainly isoprene) may increase significantly in the coming decades if short-rotation coppice plantations are expanded strongly to meet the increased biofuel demand resulting from the EU decarbonisation targets. This study investigates the competing effects of anticipated trends in land use change, anthropogenic ozone precursor emissions and climate change on European ground level ozone concentrations and related health and environmental impacts until 2050. The work is based on a consistent set of energy consumption scenarios that underlie current EU climate and air quality policy proposals: a current legislation case, and an ambitious decarbonisation case. The Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) integrated assessment model was used to calculate air pollutant emissions for these scenarios, while land use change because of bioenergy demand was calculated by the Global Biosphere Model (GLOBIOM). These datasets were fed into the chemistry transport model LOTOS-EUROS to calculate the impact on ground level ozone concentrations. Health damage because of high ground level ozone concentrations is projected to decline significantly towards 2030 and 2050 under current climate conditions for both energy scenarios. Damage to plants is also expected to decrease but to a smaller extent. The projected change in anthropogenic ozone precursor emissions is found to have a larger impact on ozone damage than land use change. The increasing effect of a warming climate (+2–5 °C across Europe in summer) on ozone concentrations and associated health damage, however, might be higher than the reduction achieved by cutting back European ozone precursor emissions. Global action to reduce air pollutant emissions is needed to make sure that ozone damage in Europe decreases towards the middle of this century

A Scalable Approach to Modelling Health Impacts of Air Pollution Based on Globally Available Data

Integrated assessment of air pollution and its impacts typically requires pre-calculated atmospheric transfer relations on a fine spatial resolution. While such concepts have been applied successfully for Europe and other regions with high data coverage, extending calculations to world regions with low local data availability is challenging and needs to be based on globally available data sets. Here we introduce a scalable approach which has been developed to expand the calculations of health impacts from exposure to ambient fine particulate matter (PM2.5) in the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) integrated assessment model to (almost) any desired region on the globe, depending on actual requirements for policy analysis. We use global sensitivity simulations of the EMEP atmospheric chemistry transport model to derive linear transfer coefficients at a resolution of 0.5 degrees. A major challenge lies in the realistic representation of inner urban PM2.5 concentrations, which depend to a large extent on local pollution sources on scales below grid resolution. We derive sub-grid concentration increments from emission densities of primary PM from low-level sources, based on (almost) globally available gridded population data with approximately 100m resolution. From ambient PM2.5 concentrations, increased risk of mortality is then calculated following the methodology of the Global Burden of Disease studies. We have implemented and validated the described approach for India, China, and Indonesia, with extensions to other G-20 member countries underway. Health impact projections under different energy policy scenarios are discussed. Due to the inherent treatment of urban areas, the effects of urbanization trends are captured explicitly, which lead to higher average population exposure as people move into polluted cities

Applying Integrated Exposure-Response Functions to PM2.5 Pollution in India

Fine particulate matter (PM2.5, diameter ≤2.5 μm) is implicated as the most health-damaging air pollutant. Large cohort studies of chronic exposure to PM2.5 and mortality risk are largely confined to areas with low to moderate ambient PM2.5 concentrations and posit log-linear exposure-response functions. However, levels of PM2.5 in developing countries such as India are typically much higher, causing unknown health effects. Integrated exposure-response functions for high PM2.5 exposures encompassing risk estimates from ambient air, secondhand smoke, and active smoking exposures have been posited. We apply these functions to estimate the future cause-specific mortality risks associated with population-weighted ambient PM2.5 exposures in India in 2030 using Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model projections. The loss in statistical life expectancy (SLE) is calculated based on risk estimates and baseline mortality rates. Losses in SLE are aggregated and weighted using national age-adjusted, cause-specific mortality rates. 2030 PM2.5 pollution in India reaches an annual mean of 74 μg/m3, nearly eight times the corresponding World Health Organization air quality guideline. The national average loss in SLE is 32.5 months (95% Confidence Interval (CI): 29.7–35.2, regional range: 8.5–42.0), compared to an average of 53.7 months (95% CI: 46.3–61.1) using methods currently applied in GAINS. Results indicate wide regional variation in health impacts, and these methods may still underestimate the total health burden caused by PM2.5 exposures due to model assumptions on minimum age thresholds of pollution effects and a limited subset of health endpoints analyzed. Application of the revised exposure-response functions suggests that the most polluted areas in India will reap major health benefits only with substantial improvements in air quality

Semantic data integration from Multi Linked Model Framework

Model integration is becoming increasingly important due to the requirements for multi-scale and multi-objective assessment and decision making. Moreover, instead of incorporating all complex related information system models that are relevant for different related aspects into one super-model, a multi linked model framework has been proposed to extract data and output from multiple linked models into the coherent data warehouse, which respects the interdependency of data from different model as well as additional knowledge already contained in its existing data cubes. In this paper, first the multi linked model framework is defined in a very formal manner. The mathematical abstract specification provides the basis for handling data exchange among various linked models as well as data from those models integrated into a data warehouse. In this context, an ETL (extract- transform-load) process has been specified to integrate data from linked models. A new feature of our approach in comparison with other ETL processes is that our transformations also require input from the data warehouse, i.e. exchanging data from linked models with the data warehouse. Hereafter, the data warehouse is developed in term of multidimensional database. While each model may keep very detailed and intermediate ('raw') data and results, the data warehouse only contains integrated data that are appropriate for the task at hand. As a proof of concept, the multi linked model framework is used to develop a common knowledge pool in term of data warehouse on the representation of socio-economic heterogeneity, and strengthen the information flows among multi linked models, e.g. population projections, energy-economic, and air pollution integrated assessment models etc., which have been developed at International Institute for Applied Systems Analysis (IIASA)

Cost-effective reductions of PM2.5 concentrations and exposure in Italy

In recent years several European air pollution policies have been based on a cost-effectiveness approach. In the European Union, the European Commission starts using the multi-pollutant, multi-effect GAINS (Greenhouse Gas Air Pollution Interactions and Synergies) model to identify cost-effective National Emission Ceilings and specific emission control measures for each Member State to reach these targets. In this paper, we apply the GAINS methodology to the case of Italy with 20 subnational regions. We present regional results for different approaches to environmental target setting for PM2.5 pollution in the year 2030. We have obtained these results using optimization techniques consistent with those of GAINS-Europe, but at a higher resolution. Our results show that an overall health-impact oriented approach is more cost-effective than setting a nation-wide limit value on ambient air quality, such as the one set for the year 2030 by the European Directive on ambient air quality and cleaner air for Europe. The health-impact oriented approach implies additional emission control costs of 153 million €/yr on top of the baseline costs, compared to 322 million €/yr for attaining the nation-wide air quality limit. We provide insights into the distribution of costs and benefits for regions within Italy and identify the main beneficiaries of a health-impact approach over a limit-value approach

Effects on well-being of investing in cleaner air in India

Over the past decade, India has experienced rapid economic growth along with increases in levels of air pollution. Our goal is to examine how alternative policies for air pollution abatement affect well-being there. In particular, we estimate the effects of policies to reduce the levels of ambient fine particulates (PM2.5), which are especially harmful to human health, on well-being, quantified using the United Nations' human development index (HDI). Two of the three dimensions of this index are based on gross domestic product (GDP) per capita and life expectancy. Our approach allows reductions in PM2.5 to affect both of them. In particular, economic growth is affected negatively through the costs of the additional pollution control measures and positively through the increased productivity of the population. We consider three scenarios of PM2.5 abatement, corresponding to no further control, current Indian legislation, and current European legislation. The overall effect in both control scenarios is that growth in GDP is virtually unaffected relative to the case of no further controls, life expectancy is higher, and well-being, as measured by the HDI, is improved. In India, air pollution abatement investments clearly improve well-being

Global anthropogenic emissions of particulate matter including black carbon

This paper presents a comprehensive assessment of historical (1990–2010) global anthropogenic particulate matter (PM) emissions including the consistent and harmonized calculation of mass-based size distribution (PM1, PM2. 5, PM10), as well as primary carbonaceous aerosols including black carbon (BC) and organic carbon (OC). The estimates were developed with the integrated assessment model GAINS, where source- and region-specific technology characteristics are explicitly included. This assessment includes a number of previously unaccounted or often misallocated emission sources, i.e. kerosene lamps, gas flaring, diesel generators, refuse burning; some of them were reported in the past for selected regions or in the context of a particular pollutant or sector but not included as part of a total estimate. Spatially, emissions were calculated for 172 source regions (as well as international shipping), presented for 25 global regions, and allocated to 0.5°  ×  0.5° longitude–latitude grids. No independent estimates of emissions from forest fires and savannah burning are provided and neither windblown dust nor unpaved roads emissions are included. We estimate that global emissions of PM have not changed significantly between 1990 and 2010, showing a strong decoupling from the global increase in energy consumption and, consequently, CO2 emissions, but there are significantly different regional trends, with a particularly strong increase in East Asia and Africa and a strong decline in Europe, North America, and the Pacific region. This in turn resulted in important changes in the spatial pattern of PM burden, e.g. European, North American, and Pacific contributions to global emissions dropped from nearly 30 % in 1990 to well below 15 % in 2010, while Asia's contribution grew from just over 50 % to nearly two-thirds of the global total in 2010. For all PM species considered, Asian sources represented over 60 % of the global anthropogenic total, and residential combustion was the most important sector, contributing about 60 % for BC and OC, 45 % for PM2. 5, and less than 40 % for PM10, where large combustion sources and industrial processes are equally important. Global anthropogenic emissions of BC were estimated at about 6.6 and 7.2 Tg in 2000 and 2010, respectively, and represent about 15 % of PM2. 5 but for some sources reach nearly 50 %, i.e. for the transport sector. Our global BC numbers are higher than previously published owing primarily to the inclusion of new sources. This PM estimate fills the gap in emission data and emission source characterization required in air quality and climate modelling studies and health impact assessments at a regional and global level, as it includes both carbonaceous and non-carbonaceous constituents of primary particulate matter emissions. The developed emission dataset has been used in several regional and global atmospheric transport and climate model simulations within the ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) project and beyond, serves better parameterization of the global integrated assessment models with respect to representation of black carbon and organic carbon emissions, and built a basis for recently published global particulate number estimates

Investment perspectives on costs for air pollution control affect the optimal use of emission control measures

Cost-effective air pollution emission control has been in focus for decades in international air pollution regulations. Despite large observed emission reductions for many air pollutants, environmental and human health problems persist and more efforts are needed. However, some stakeholders are concerned that the costs for remaining emission control measures are prohibitively high. There are several reasons for concern, and one can be the difference in investment perspectives—i.e. costs of borrowing and time constraints—held by stakeholders. By using the integrated assessment model GAINS, we study whether differences in investment perspectives of Nordic stakeholders influence measures selected for cost-effective emission control and can motivate concerns for high costs of emission control. We distinguish the control cost calculations between a social planner perspective and a corporate perspective and apply these to the GAINS model database on emission control measures. A cost-minimized selection of measures in 2030 is then calculated for increasing environmental and health ambitions for both perspectives. The results show an irregular pattern, but for a range of ambition levels the corporate perspective affects the selection of measures and implies surplus costs for the Nordic social planner of up to 120 million € per year. This is 36% more expensive than the costs of the social planners’ selection. Conversely, from a corporate perspective the social planners’ selection can imply cost increases of up to 180 million €. We therefore suggest that control of investment perspective effects should be standard in analysis of cost-effective air pollution measures