The evolution of mass balance models of persistent organic pollutant fate in the environment

Current approaches to modelling the fate of persistent organic pollutants (POPs) in the environment have evolved in response to four dominant characteristics of these substances; namely: (1) the presence of POPs in virtually all environmental phases and the ease with which they move from one to the other requires multi-compartmental modelling. Describing transport across phase boundaries becomes as, or even more, important as quantifying transport within the phases; (2) POPs may persist in the environment for many decades. For chemicals that 'have time', concepts such as equilibrium partitioning and steady-state become more important than for short-lived substances whose fate is more controlled by the rates of transformation; (3) measuring POPs is difficult and expensive and observed concentrations of POPs are not available in high spatial or temporal resolution. Consequently, high resolution tends not to be a high priority in POP models; and (4) detrimental effects of POPs often manifest themselves in top predators, which has led to a focus on modelling biotic uptake and transfer within food chains. The task of building a POPs model is viewed as combining the four 'building blocks' of partitioning, transport, transformation and source data with the help of the law of the conservation of mass. Process models, evaluative models, models of real local, regional and global fate, as well as biological uptake models are presented and references to numerous examples are provided. An attempt is made to forecast future directions in the field of POPs modelling. It is expected that modelling techniques that do not rely on quantitative emission estimates as well as approaches that take into account spatial, temporal and climatic variability as well as parameter uncertainty will increase in importance. Finally, the relationship between modelling POPs and models of other pollutant issues is addressed, as are potential interactions between POPs and pollutant issues such as eutrophication, acidification and global climate change.     

Climate change influence on POPs distribution and fate: a case study

Climate change has the potential of affecting the behaviour and distribution of organic pollutants, including POPs. Direct effects of climate change, like temperature increase, modification of wind and precipitation patterns, sea level rise, snow and ice cover, may be very effective in altering the partitioning of POPs among the environmental compartments. Other consequences of future climate scenarios may imply the alteration of degradation rates, soil properties (and hence land use), air-particle partitioning of chemicals and so forth. A case study is here presented to illustrate the major implications of climate change on the long term at the local scale. A dynamic multimedia model was applied to selected PCB and PCDD/F congeners to simulate the effects of climate change on their distribution and fluxes over the next 50 y in the Venice Lagoon (Italy). Different climate change scenarios were tested, finding noticeable variations in POPs concentration even for minor environmental changes. PCBs and PCDFs environmental concentrations may differ by a factor two in a moderate climate change scenario, compared to a situation with stable climate over the next 50 y. However, model results also suggest that if global warming may have the potential of reducing the environmental levels of these chemicals, it would probably enhance their mobility and hence their potential for long range atmospheric transport.     

Forests under climate change and air pollution: gaps in understanding and future directions for research

Forests in Europe face significant changes in climate, which in interaction with air quality changes, may significantly affect forest productivity, stand composition and carbon sequestration in both vegetation and soils. Identified knowledge gaps and research needs include: (i) interaction between changes in air quality (trace gas concentrations), climate and other site factors on forest ecosystem response, (ii) significance of biotic processes in system response, (iii) tools for mechanistic and diagnostic understanding and upscaling, and (iv) the need for unifying modelling and empirical research for synthesis. This position paper highlights the above focuses, including the global dimension of air pollution as part of climate change and the need for knowledge transfer to enable reliable risk assessment. A new type of research site in forest ecosystems ("supersites") will be conducive to addressing these gaps by enabling integration of experimentation and modelling within the soil-plant-atmosphere interface, as well as further model development.     

Changes in extreme events and the potential impacts on human health

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.

Implications: Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.     

Greenhouse gas induced climate change

Simulations using global coupled climate models predict a climate change due to the increasing concentration of greenhouse gases and aerosols in the atmosphere. Both are associated with the burning of fossil fuels. There has been considerable debate if this postulated human influence is already evident. This paper gives an overview on some recent material on this question. One particular study using optimal fingerprints (Hegerl et al., 1996) is explained in more detail. In this study, an optimal fingerprint analysis is applied to temperature trend patterns over several decades. The results show the probability being less than 5% that the most recently observed 30 year trend is due to naturally occurring climate fluctuations. This result suggests that the present warming is caused by some external influence on climate, e.g. by the increasing concentrations of greenhouse gases and aerosols. More work is needed to address the uncertainties in the magnitude of naturally occurring climate fluctuations. Also, other external influences on climate need to be investigated to uniquely attribute the present climate change to the human influence.     

Part IV: Fitness for Aquatic Systems Long-term Forecast: Key to groundwater protection

Groundwater resources are at risk from pollution, climate change and land-management practices. Long-term forecast is a tool to demonstrate future development and to support decisions on measures which can be implemented, controlled and eventually corrected. As the basis for preventive action, a forecast can be viewed as a key to groundwater protection. The soil zone plays a vital role in groundwater protection. Research on soil and groundwater trends, as affected by change of climate and/or land-management practices, is on the agenda. Integrated research is necessary to develop numerical soil-water system models reflecting all relevant transport processes at various scales. Even relatively simple problems like forecasting pollutant release from contaminated materials are difficult to resolve. Batch tests may be sufficient in low-risk cases. At higher risk when contaminated substrates are chosen for deposition on a large scale, a thorough characterization of the materials is necessary covering all aspects of stability and possible changes of the environment.     

Status and trends in Arctic vegetation: Evidence from experimental warming and long-term monitoring

Changes in Arctic vegetation can have important implications for trophic interactions and ecosystem functioning leading to climate feedbacks. Plot-based vegetation surveys provide detailed insight into vegetation changes at sites around the Arctic and improve our ability to predict the impacts of environmental change on tundra ecosystems. Here, we review studies of changes in plant community composition and phenology from both long-term monitoring and warming experiments in Arctic environments. We find that Arctic plant communities and species are generally sensitive to warming, but trends over a period of time are heterogeneous and complex and do not always mirror expectations based on responses to experimental manipulations. Our findings highlight the need for more geographically widespread, integrated, and comprehensive monitoring efforts that can better resolve the interacting effects of warming and other local and regional ecological factors.     

Climate of the earth: an overview

Climate has varied over a large range in the recent history of the Earth, with extremes represented by equable environments of the Cretaceous and Eocene and the comparatively frigid conditions of the ice ages that punctuated the past few million years. It is suggested that major shifts in climate are controlled largely by variations in CO(2) with related fluctuations in modes of ocean circulation. Changes in climate can proceed rapidly, on time scales as short as centuries or even decades, as indicated by data for the Younger Dryas (a period of globally cold conditions interrupting recovery of the Earth from the last ice age) and the Little Ice Age (a cold snap extending from about 1250 to about 1850 ad). Rapid fluctuations in climate appear to be linked to changes in production of deep water in the North Atlantic, possibly also to variations in circulation of intermediate waters in the Pacific. Mechanisms are discussed whereby changes in ocean circulation can result in shifts of climate on a global scale. A 10 000 year record of climate from Norway is used to provide context for a discussion of possible changes in climate today arising as a result of the build-up of industrially related greenhouse gases. Brief, somewhat pessimistic, comments are offered concerning the prospects for meaningful near-term predictions of the response of climate to increased concentrations of greenhouse gases. Studies of past climates, by drawing attention to important processes and feedbacks, can play a valuable role in the development of credible models for the future.     

Vertical distribution of organochlorine pesticides in humus along Alpine altitudinal profiles in relation to ambiental parameters

In forest soils along vertical profiles located in different parts of the Alps, concentrations of persistent organic pollutants (POPs), namely organochlorine pesticides (OCPs) like dichlorodiphenyltrichloroethanes (DDTs), hexachlorobenzene (HCB), hexachlorocyclohexanes (HCH), heptachlor, aldrin, dieldrin and mirex, were measured. Though local characteristics of the sites are influenced by numerous factors like orographic and meteorological parameters, forest stand characteristics and humus parameters, we ascertained a marked vertical increase of concentrations of some organochlorine compounds in the soil. On the basis of climatological values of each site, we found that the contamination increase with altitude can be ascribed to a certain ‘cold condensation effect’. In addition, the perennial atmospheric deposition of POPs is controlled by precipitation. Other key parameters explaining the accumulation of POPs are the soil organic carbon stocks, the turnover times, the re-volatilisation and degradation processes, which vary with altitude.     

Increase in summer European ozone amounts due to climate change

The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.     

Adapting air quality management for a changing climate: Survey of local districts in California

Air quality can be affected by weather and thus is sensitive to a changing climate. Wildfire (influenced by weather), consecutive high temperature summer days, and other extreme events are projected to become more severe and frequent with climate change. These may create challenging conditions for managing air quality despite policy targets to reduce precursor and pollutant emissions. Although extreme events are becoming more intense and interest in climate adaptation is increasing among public health practitioners, little attention in scholarly literature and policy covers climate adaptation for air quality governance. Understanding the management and managers’ perspectives at the local level provides insight about the needs for climate adaptation, including their adaptation status, perspectives, responsibilities, and roles. This study explores local manager perspectives and experiences of managing air quality within a changing climate as one puzzle piece to understand the gap in climate adaptation within the air quality sector. A broader goal is to contribute to the discussion of developing a multi-jurisdictional vision for reducing the impacts of air quality in a changing climate. In 2016 local air quality district managers in California were invited to participate in an online survey of 39 questions focused on extreme event impacts on air quality. The questionnaire focused on present air quality threats and extreme event challenges, adaptation status and strategies, adaptive capacities, perceived barriers to adaptation, and jurisdictional responsibilities and roles. Over 85 percent of the 35 local air districts in California participated in the survey, which represents 80 percent of the state’s population. High awareness and knowledge of climate change among local managers indicates they are ready to adopt and take action on policies that would support climate adaptation, but barriers reported suggests they may need policies and adequate funding to take action and make necessary changes.

Implications: Downscaled global climate models project an increasing severity and frequency of extreme events. In the southwestern United States, these include wildfire, heat events, and dry periods, among others, all of which can place an extra burden on air quality managers and emitters to achieve air quality standards even as they reduce emissions. Despite climate change presenting increasing challenges to meet air quality standards, in the southwestern United States, policy and action to mitigate these impacts have been surprisingly absent. California presents a valuable case study on the topic because of its historic leadership in air quality management for the United States and also because of its initiatives in combating climate change. Yet still we found that adaptation has not been incorporated into air quality management thus far, but local managers seem sufficiently knowledgeable and willing.     

Climate change impact on distribution and abundance of wildlife species: an analytical approach using GIS

An analytical approach to modelling the likely impact of climate change on the distribution and abundance of wildlife species is described using examples from Scotland. Data for present day distribution of wildlife and habitat are analysed using map data describing geographic variation in climatic factors. Climate data for the present day and under specified scenarios of change are themselves modelled within a GIS; climate modelling uses meteorological station data, climate change scenarios developed from GCMs and a variety of spatial interpolation techniques. The analytical procedure generates hypotheses defining ecological relationships between species distribution and climatic factors (monthly, seasonal and annual data). These relationships are then used to model the distribution of the species directly from climate and predict impacts of climate change. The analysis takes account of both direct impacts of climate on wildlife and indirect effects manifested through habitat response to climate change. The analytical procedure is implemented as a generic tool for inductive spatial analysis in GIS.     

Simulating uncertainty in climate-pest models with fuzzy numbers

Inputs in climate-pest models are commonly expressed as point estimates ('crisp' numbers), which implies perfect knowledge of the system in study. In reality, however, all model inputs harbor some level of uncertainty. This is particularly true for climate change impact assessments where the inputs (i.e., climate projections) are highly uncertain. In this study, uncertainties in climate projections were expressed as 'fuzzy' numbers; these are uncertain numbers for which one knows that there is a range of possible values and that some values are 'more possible' than others. A generic pest risk model incorporating the combined effects of temperature, soil moisture, and cold stress was implemented in a fuzzy spreadsheet environment and run with three climate scenarios: (1) present climate (control run); (2) crisp climate change; and (3) fuzzy climate change. Under the crisp climate change scenario, winter and summer temperatures and precipitation were altered using best estimates (averaged predictions from the 1995 assessment report of the Intergovernmental Panel on Climate Change [IPCC]). Under the fuzzy scenario, climate changes were expressed as triangular fuzzy numbers, utilizing the extremes (lowest and highest predictions from the IPCC report) in addition to the best estimates. Under each scenario, environmental favorability was calculated for six locations in two geographical regions (Central North America and Southern Europe) with two hypothetical pest species having temperate or mediterranean climate requirements. Simulations with the crisp climate change scenario suggested only minor changes in overall environmental favorability compared with the control run. When simulations were conducted with the fuzzy climate change scenario, however, important changes in environmental favorability emerged, particularly in Southern Europe. In that region, the possibility of considerably increased winter precipitation led to increased values of environmental favorability. However, the simulations also showed that this result harbored a very broad range of possible outcomes. The results support the notion that uncertainty in climate change projections must be reduced before reliable impact assessments can be achieved.     

Tipping Points in the Arctic: Eyeballing or Statistical Significance?

Arctic ecosystems have experienced and are projected to experience continued large increases in temperature and declines in sea ice cover. It has been hypothesized that small changes in ecosystem drivers can fundamentally alter ecosystem functioning, and that this might be particularly pronounced for Arctic ecosystems. We present a suite of simple statistical analyses to identify changes in the statistical properties of data, emphasizing that changes in the standard error should be considered in addition to changes in mean properties. The methods are exemplified using sea ice extent, and suggest that the loss rate of sea ice accelerated by factor of ~5 in 1996, as reported in other studies, but increases in random fluctuations, as an early warning signal, were observed already in 1990. We recommend to employ the proposed methods more systematically for analyzing tipping points to document effects of climate change in the Arctic.     

High Arctic ecosystem states: Conceptual models of vegetation change to guide long-term monitoring and research

Vegetation change has consequences for terrestrial ecosystem structure and functioning and may involve climate feedbacks. Hence, when monitoring ecosystem states and changes thereof, the vegetation is often a primary monitoring target. Here, we summarize current understanding of vegetation change in the High Arctic—the World’s most rapidly warming region—in the context of ecosystem monitoring. To foster development of deployable monitoring strategies, we categorize different kinds of drivers (disturbances or stresses) of vegetation change either as pulse (i.e. drivers that occur as sudden and short events, though their effects may be long lasting) or press (i.e. drivers where change in conditions remains in place for a prolonged period, or slowly increases in pressure). To account for the great heterogeneity in vegetation responses to climate change and other drivers, we stress the need for increased use of ecosystem-specific conceptual models to guide monitoring and ecological studies in the Arctic. We discuss a conceptual model with three hypothesized alternative vegetation states characterized by mosses, herbaceous plants, and bare ground patches, respectively. We use moss-graminoid tundra of Svalbard as a case study to discuss the documented and potential impacts of different drivers on the possible transitions between those states. Our current understanding points to likely additive effects of herbivores and a warming climate, driving this ecosystem from a moss-dominated state with cool soils, shallow active layer and slow nutrient cycling to an ecosystem with warmer soil, deeper permafrost thaw, and faster nutrient cycling. Herbaceous-dominated vegetation and (patchy) bare ground would present two states in response to those drivers. Conceptual models are an operational tool to focus monitoring efforts towards management needs and identify the most pressing scientific questions. We promote greater use of conceptual models in conjunction with a state-and-transition framework in monitoring to ensure fit for purpose approaches. Defined expectations of the focal systems’ responses to different drivers also facilitate linking local and regional monitoring efforts to international initiatives, such as the Circumpolar Biodiversity Monitoring Program.     

Effect of climate change on flux of N and C: air-land-freshwater-marine links: synthesis

Projected climate change might increase the deposition of nitrogen by about 10% to seminatural ecosystems in southern Norway. At Storgama, increased precipitation in the growing season increased the fluxes of total organic carbon (TOC) and total organic nitrogen (TON) in proportion to the water flux. In winter, soil temperatures near 0 degrees C, common under a snowpack, induced higher runoff of inorganic nitrogen (N) and lower runoff of TOC. By contrast, soil temperatures below freezing, caused by little snow accumulation (expected in a warmer world), reduced runoff of inorganic N, TON, and TOC. Long-term monitoring data showed that reduced snowpack can cause either decreased or increased N leaching, depending on interactions with N deposition, soil temperature regime, and winter discharge. Seasonal variation in TOC was mainly climatically controlled, whereas deposition of sulfate and nitrate (NO3) explained the long-term TOC increase. Upscaling to the river basin scale showed that the annual flux of NO3 will remain unchanged in response to climate change projections.     

Hydrological change--climate change impact simulations for Sweden

Climate change resulting from the enhanced greenhouse effect is expected to give rise to changes in hydrological systems. This hydrological change, as with the change in climate variables, will vary regionally around the globe. Impact studies at local and regional scales are needed to assess how different regions will be affected. This study focuses on assessment of hydrological impacts of climate change over a wide range of Swedish basins. Different methods of transferring the signal of climate change from climate models to hydrological models were used. Several hydrological model simulations using regional climate model scenarios from Swedish Regional Climate Modelling Programme (SWECLIM) are presented. A principal conclusion is that subregional impacts to river flow vary considerably according to whether a basin is in northern or southern Sweden. Furthermore, projected hydrological change is just as dependent on the choice of the global climate model used for regional climate model boundary conditions as the choice of anthropogenic emissions scenario.     

Socio-economic vulnerability to climate change in the central mountainous region of eastern Mexico

Climate change effects are expected to be more severe for some segments of society than others. In Mexico, climate variability associated with climate change has important socio-economic and environmental impacts. From the central mountainous region of eastern Veracruz, Mexico, we analyzed data of total annual precipitation and mean annual temperature from 26 meteorological stations (1922–2008) and from General Circulation Models. We developed climate change scenarios based on the observed trends with projections to 2025, 2050, 2075, and 2100, finding considerable local climate changes with reductions in precipitation of over 700 mm and increases in temperature of ~9°C for the year 2100. Deforested areas located at windward were considered more vulnerable, representing potential risk for natural environments, local communities, and the main crops cultivated (sugarcane, coffee, and corn). Socio-economic vulnerability is exacerbated in areas where temperature increases and precipitation decreases.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0690-4) contains supplementary material, which is available to authorized users.     

Global change and the boreal forest: thresholds, shifting states or gradual change?

Changes in boreal climate of the magnitude projected for the 21st century have always caused vegetation changes large enough to be societally important. However, the rates and patterns of vegetation change are difficult to predict. We review evidence suggesting that these vegetation changes may be gradual at the northern forest limit or where seed dispersal limits species distribution. However, forest composition may be quite resilient to climate change in the central portions of a species range until some threshold is surpassed. At this point, changes can be rapid and unexpected, often causing a switch to very different ecosystem types. Many of these triggers for change are amenable to management, suggesting that our choice of policies in the coming decades will substantially influence the ecological and societal consequences of current climatic change.     

Uncertainty assessment of spatial patterns of soil organic carbon density using sequential indicator simulation, a case study of Hebei province, China

The spatial patterns of soil organic carbon (SOC) are closely related to the global climate change. In quantifying the spatial patterns of SOC density, the concept of uncertainty of the SOC density values at unsampled locations is particularly important because such uncertainty can be propagated into the subsequent global climate change modelling and has fundamental impacts on the ultimate results of the model. A total of 361 SOC density data of topsoil (0–20 cm) in Hebei province and sequential indicator simulation (SIS) were applied to perform a conditional stochastic simulation in this study to quantitatively assess the uncertainty of mapping SOC density. The results showed that a great variation exists in the SOC density data. The conditional variance of 500 realizations generated by SIS was larger in mountainous areas of the study area where the SOC density fluctuated the most, and the uncertainty was smaller on the plain area where SOC density was consistently small. Realizations generated by SIS can represent the possible spatial patterns of SOC density without smoothing effect. A set of realizations can be used to explore all possible spatial patterns of SOC density and provide a visual and quantitative measure of the spatial uncertainty of mapping SOC density. With a given threshold of SOC density, SIS can quantitatively assess both local uncertainty and spatial uncertainty of SOC density that is greater the threshold.