Climate Change-induced Changes Research Articles

A multi-scenario multi-model analysis of regional climate projections in a Central–Eastern European agricultural region: assessing shallow groundwater table responses using an aggregated vertical hydrological model

The 2022 drought highlighted Hungary's vulnerability to climate change, especially the Great Hungarian Plain. Soil moisture, which is crucial for agriculture, depends on the position of the shallow groundwater table. This study investigated the effects of climate change on groundwater table fluctuations in more than 500 wells on the plain. An integrated vertical hydrological model, assuming negligible horizontal subsurface flows, employed the Dunay–Varga-Haszonits methodology for evaporation and Kovács approach for the water retention curve. Verified with two meteorological databases, the model was accepted for 463 wells based on NSE > 0.4 and RMSE < 0.5 m criteria. The FORESEE HUN v1.0 dataset proved suitable after spatial consistency tests. Examining 28 bias- and discontinuity-corrected climate model projections on these wells revealed a general decline in the groundwater table. Differences between trends to 2050 and 2100 suggested lower groundwater levels by mid-century. This research highlights climate change impacts in a crucial Central-European agricultural region in the Carpathian Basin and emphasizes the importance of modeling climate change-induced changes in shallow groundwater levels in water resources management.

Flood vulnerability assessment in the flood prone area of Khyber Pakhtunkhwa, Pakistan

Floods are among the most destructive natural disasters, causing extensive damage to human lives, property, and the environment. Pakistan is susceptible to natural calamities, such as floods, resulting in millions of people being impacted yearly. It has been demonstrated that flood severity is rising and may continue to escalate in the coming years because of climate change-induced changes in monsoon precipitation in the country. Given the country’s exposure to flooding, it is essential to assess the vulnerability to floods to prepare for and mitigate their impact in Pakistan. This study provides a new conceptual framework for assessing flood risk and vulnerability in Charsadda, a flood-prone district in Pakistan. It evaluates the vulnerability of settlements to floods based on four indicators: population density, the average gross domestic product (GDP) of land, the distance between settlements and rivers, and land use and cover (LULC). The analytical hierarchy process (AHP) technique was integrated with the geographical information system (GIS) to assess the level of vulnerability to floods in the study area. The results reveal a higher degree of vulnerability to floods in the region. The spatial pattern of vulnerable areas reveals a significant connection between high-risk flood areas and densely populated areas during different flood seasons. The results further reveal that more than 60% of the area is arable land and is highly susceptible to flood. The population and their land-use setup show high and extremely high values of vulnerability in the normalized threshold of 0.3–0.4, respectively. The study provides an in-depth and comprehensive analysis of the chosen indicators, evaluation methods, and results, making this a valuable contribution to the field of flood vulnerability assessment. The findings of this study also include thematic maps and related information to the stakeholders for effective vulnerability management in the study area.

Satellite remote sensing can provide semi-automated monitoring to aid coastal decision-making

Coastlines are projected to face unprecedented pressures over the next century due to climate change-induced changes in sea level, storm, wave, and tidal regimes. This projection of increasing pressure is driving a reappraisal of existing shoreline management practices, with both science and policy calling for future strategies to work with the natural protection provided by coastal habitats such as salt marshes. However, we currently lack the understanding of long-term ecosystem dynamics required to incorporate these habitats into the definitive predictions of risk relied on in coastal protection planning. Satellite remote sensing has the potential to provide data that could address this knowledge gap with its frequent repeat times and global coverage facilitating the production of high temporal frequency time-series over large areas. This study sought to explore this potential in one of the largest coastal plain estuaries the in the UK, the Severn Estuary. The Random Forest machine learning algorithm was used to develop a time-series of marsh extents across the estuary from 1985 to 2020 in Google Earth Engine, with widths also extracted as a proxy for the marshes’ protective capacity. These changes were monitored in six areas that contained the most significant areas of salt marsh across the estuary. This analysis revealed a significant increasing trend in extent and widths (p < 0.05), and therefore natural coastal protection, in three of the six areas over the study period, with validation testing finding an overall accuracy for the classification of >90% and a strong agreement found between the detected widths and those found in previous surveys. These findings demonstrate that satellite remote sensing combined with machine learning has the potential to provide valuable insights into changes in the extents of marshes and therefore their protective capacity. This information can be useful in the coastal planning process, allowing decision-makers to assess the sustainability of existing defences fronted by marshes, as well as allowing them to make informed decisions about the location of restoration schemes.

Impacts Of Changes in Vegetation Structure on Elephant Habitat and Relationship to Human Conflict

With global climate change, ecosystems and biodiversity are facing unprecedented threats. Yunnan, as an important region for biodiversity, is experiencing significant vegetation structural changes, which have far-reaching impacts on its endemic elephant populations. This study focuses on how climate change-induced changes in vegetation structure affect Yunnan's elephant habitat and its conflict with humans. The study found that the elephants' traditional habitats have been severely fragmented due to climate change-induced forest degradation and grassland changes, forcing them to engage in more frequent conflicts with the local residents. This ecological change not only threatens the survival of elephants, but also puts enormous economic and livelihood pressures on the local communities. In addition, elephants' migration routes and behavioral patterns have been significantly altered as a result. This study reveals the complex impacts of climate change on biodiversity and human life, and emphasizes the urgency of taking appropriate measures to protect the ecological balance.

Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea

Abstract. Extreme sea level events, such as storm surges, pose a threat to coastlines around the globe. Many tide gauges have been measuring the sea level and recording these extreme events for decades, some for over a century. The data from these gauges often serve as the basis for evaluating the extreme sea level statistics, which are used to extrapolate sea levels that serve as design values for coastal protection. Hydrodynamic models often have difficulty in correctly reproducing extreme sea levels and, consequently, extreme sea level statistics and trends. In this study, we generate a 13-member hindcast ensemble for the non-tidal Baltic Sea from 1979 to 2018 using the coastal ocean model GETM (General Estuarine Transport Model). In order to cope with mean biases in maximum water levels in the simulations, we include both simulations with and those without wind-speed adjustments in the ensemble. We evaluate the uncertainties in the extreme value statistics and recent trends of annual maximum sea levels. Although the ensemble mean shows good agreement with observations regarding return levels and trends, we still find large variability and uncertainty within the ensemble (95 % confidence levels up to 60 cm for the 30-year return level). We argue that biases and uncertainties in the atmospheric reanalyses, e.g. variability in the representation of storms, translate directly into uncertainty within the ensemble. The translation of the variability of the 99th percentile wind speeds into the sea level elevation is in the order of the variability of the ensemble spread of the modelled maximum sea levels. Our results emphasise that 13 members are insufficient and that regionally large ensembles should be created to minimise uncertainties. This should improve the ability of the models to correctly reproduce the underlying extreme value statistics and thus provide robust estimates of climate change-induced changes in the future.

Molecular and functional characterization of chemosensory genes from the root-knot nematode Meloidogyne graminicola

BackgroundRoot-knot nematode Meloidogyne graminicola has emerged as a major threat in rice agroecosystems owing to climate change-induced changes in cultivation practices. Synthetic nematicides are continually being withdrawn from the nematode management toolbox because of their ill effects on the environment. A sustainable strategy would be to develop novel nematicides or resistant plants that would target nematode sensory perception, which is a key step in the host finding biology of plant-parasitic nematodes (PPNs). However, compared to the extensive literature on the free-living nematode Caenorhabditis elegans, negligible research has been performed on PPN chemosensory biology.ResultsThe present study characterizes the five chemosensory genes (Mg-odr-7, Mg-tax-4, Mg-tax-4.1, Mg-osm-9, and Mg-ocr-2) from M. graminicola that are putatively associated with nematode host-finding biology. All the genes were highly transcribed in the early life stages, and RNA interference (RNAi)-induced downregulation of each candidate gene perturbed the normal behavioural phenotypes of M. graminicola, as determined by examining the tracking pattern of juveniles on Pluronic gel medium, attraction to and penetration in rice root tip, and developmental progression in rice root. In addition, a detrimental effect on nematode chemotaxis towards different volatile and nonvolatile organic compounds and host root exudates was documented.ConclusionOur findings enrich the existing literature on PPN chemosensory biology and can supplement future research aimed at identifying a comprehensive chemosensory signal transduction pathway in PPNs.

The correlation of climate change and mortality: climate change as a factor for health inequalities

Abstract Recent research has found robust evidence that climate change is often negatively impacting on human health. These impacts are distributed spatially unequal both across the countries of the world and within the countries. While research has clearly outlined this unequal distribution on the country level, for instance with the recently added non-optimal temperature risk factor of the Global Burden of Disease 2019 dataset, thereby acknowledging the impact of unfavorable average temperatures on health, the spatial differences in climate change impacts on health on the subnational level is hardly researched. By operationalizing climate data for a climate change trend analysis of various climate change parameters in GIS, and by applying mortality data for different high-, low-, and middle-income countries on administrative area level 2 for both an Ordinary Least Squared (OLS) and Geographically Weighted (GWR) regression analysis, the proposed article is analyzing the unequal impact of climate change on health inequalities within different countries. Under the assumption that climate change-induced changes of local climate-related conditions affect those areas that already are in a disadvantaged position when it comes to health inequality, the paper is expected to show that inequality gaps are further widening due to climate change, not only but especially in low- and middle-income countries that are more affected by climate change than most of the high-income countries. Therefore, it will have to be discussed, how these increasing health inequalities can be dealt with in a just way and under consideration of already existing vulnerabilities in the most affected areas of climate change. Key messages • Climate change directly influences mortality in all analyzed countries with a bigger impact on low- and middle-income countries. • Climate change contributes to widening health inequalities on a subnational level and especially in low- and middle-income countries.

Impact of climate change on non-communicable diseases caused by altered UV radiation.

UV radiation can cause serious skin and eye diseases, especially cancers. UV-related skin cancer incidences have been increasing for decades. The determining factor for this development is the individual UV exposure. Climate change-induced changes in atmospheric factors can influence individual UV exposure. On the basis of a topic-specific literature research, a review paper was prepared and supplemented by as yet unpublished results of the authors' own studies. The need for scientific research and development is formulated as well as primary prevention recommendations. Climate change alters the factors influencing UV irradiance and annual UV dose in Germany. First evaluations of satellite data for Germany show an increase in mean peak UV irradiance and annual UV dose for the last decade compared to the last three decades. The climate change-related influences on individual UV exposure and the associated individual disease incidence cannot yet be reliably predicted due to considerable uncertainties. However, the current UV-related burden of disease already requires primary preventive measures to prevent UV-related diseases.

Where have all the petrels gone? Forty years (1978–2020) of Wilson’s Storm Petrel (Oceanites oceanicus) population dynamics at King George Island (Isla 25 de Mayo, Antarctica) in a changing climate

Numerous seabird species are experiencing population declines, and this trend is expected to continue or even accelerate in the future. To understand the effects of environmental change on seabird populations, long-term studies are vital, but rare. Here, we present over four decades (1978–2020) of population dynamic and reproductive performance data of Wilson’s Storm Petrels (Oceanites oceanicus) from King George Island (Isla 25 de Mayo), Antarctica. We determined temporal trends in population size, breeding output, and chick growth rates, and related interannual variation in these variables to various environmental variables. Our study revealed a decline of 90% in population size of Wilson’s Storm Petrels in two colonies, and considerable changes in breeding output and chick growth rates. Temporal changes in breeding demographics were linked to interannual environmental variation, either causing changes in food availability (particularly Antarctic krill, Euphausia superba) or in nest burrow accessibility due to snow blocking the entrance. With the expected rise in air and sea surface temperatures, the predicted increases in precipitation over the Antarctic Peninsula will likely lead to increased snowstorm prevalence. Additionally, the rising temperatures will likely reduce food availability due to reduced sea ice cover in the wintering grounds of Antarctic krill, or by changing phyto- and zooplankton community compositions. The ongoing environmental changes may thus lead to a further population decline, or at the very least will not allow the population to recover. Monitoring the population dynamics of Antarctic seabirds is vital to increase our understanding of climate change-induced changes in polar food webs.

Are the IPCC’s findings encouraging climate action in sub-Saharan Africa?

Recently, the Intergovernmental Panel on Climate Change (IPCC) released Part I of its Sixth Assessment Report. While the report is comprehensive in outlining the climate change-induced changes to the physical environment, one wonders how relevant such information is to African policymakers planning for the next generation.

Feasibility, acceptability and validation of wearable devices for climate change and health research in the low-resource contexts of Burkina Faso and Kenya: Study protocol.

As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population's burden of disease. The burden of disease of climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vulnerable populations, such as heat stress on human cardiovascular response. The overall goal of this study is to investigate whether consumer-grade wearable devices are an acceptable, feasible and valid means to generate data on the individual level in low-resource contexts. Three hundred individuals are recruited from the two study locations in the Nouna health and demographic surveillance system (HDSS), Burkina Faso, and the Siaya HDSS, Kenya. Participants complete a structured questionnaire that comprises question items on acceptability and feasibility under the supervision of trained data collectors. Validity will be evaluated by comparing consumer-grade wearable devices to research-grade devices. Furthermore, we will collect demographic data as well as the data generated by wearable devices. This study will provide insights into the usage of consumer-grade wearable devices to measure individual vital signs in low-resource contexts, such as Burkina Faso and Kenya. Vital signs comprising activity (steps), sleep (duration, quality) and heart rate (hr) are important measures to gain insights on individual behavior and activity patterns in low-resource contexts. These vital signs may be associated with weather variables-as we gather them from weather stations that we have setup as part of this study to cover the whole Nouna and Siaya HDSSs-in order to explore changes in behavior and other variables, such as activity, sleep, hr, during extreme weather events like heat stress exposure. Furthermore, wearable data could be linked to health outcomes and weather events. As a result, consumer-grade wearables may serve as a supporting technology for generating reliable measurements in low-resource contexts and investigating key links between weather occurrences and health outcomes. Thus, wearable devices may provide insights to better inform mitigation and adaptation interventions in these low-resource settings that are direly faced by climate change-induced changes, such as extreme weather events.

Changes in the Montagu's Harrier Circus pygargus diet in Eastern Poland across decades promote insects and reptilians, but not birds and rodents.

We investigated temporal changes in diet composition of the Montagu's Harrier Circus pygargus breeding in natural habitat (calcareous peat bog) in SE Poland. We characterized diet composition in a three‐year period (2007–2009), based on pellet analyses. We investigated whether diet composition was affected by years or stage of breeding. We compared diet of the studied population between 2000s and 1990s and with other populations. We found that the food of the studied population was dominated by insects and mammals (by number) and mammals and birds (by biomass). Biomass and abundance of main prey items differed between studied years because of different air temperatures. We found some interannual differences in contribution of some prey items including higher number of thermophilic prey (insects and amphibians) in warmer years. Comparison of pellet composition in the 1990s and 2000s revealed significant increase in the abundance of thermophilic prey (insects and reptiles) and decrease of mammals including Microtus voles and birds. Those changes may be linked to habitat changes in areas neighboring peat bogs and climate change‐induced changes in prey communities. The studied population was able to respond to changes in foraging habitats and prey composition by opportunistic foraging on easily available prey. The diet of the studied population is the most similar to the geographically closest populations foraging in similar habitats and characterized by high contribution of insects.

Climate Change-Induced Changes in the Chemistry of a High-Altitude Mountain Lake in the Central Alps

Mountains are among the most sensitive ecosystems to climate change, and one of the most evident signs of climate-related effect is the continuous net loss of ice from the cryosphere. Several studies showed that meltwater from glaciated and perennially frozen areas can profoundly affect alpine aquatic ecosystems. Here, we present the impressive temporal increase in solutes in Lake Leit, a mountain lake in the Central Alps that is impacted by an active rock glacier. During the last 30 years, concentrations of sulfate and base cations increased by factors of 4 and 3, respectively. Atmospheric deposition, the only catchment external source, could be excluded as possible cause. The inlets have sulfate and base cations concentrations that were up to double the concentrations of the lake outlet confirming the presence of catchment internal sources. The highest concentrations were measured in the springs at the bottom of the rock glacier. Ground surface temperatures of the rock glacier indicated a high probability of permafrost occurrence, while the annual mean air temperature after the mid-1980s showed continuously positive deviations from the long-term average values (period 1961–1990) with increasing values after 2010. δ34S of sulfate in the inlets and the outflow indicated that sulfate in Lake Leit mainly derived from dissolution of gypsum/anhydrite even if its presence is not confirmed by the Geologic Atlas of Switzerland. Because of these results, we postulate the presence of subsurface traces of sulfate-bearing evaporites, probably associated with Triassic metasediments. These deposits are very common in the closer surroundings. We further hypothesize that the thawing of permafrost affects the flow path of water enabling its contact with fresh highly weatherable minerals increasing the overall weathering rate and shifting the relative ionic composition in the discharge toward the ions that originate from the most soluble minerals. This study shows that increased permafrost thawing in the future can influence water quality in high-alpine settings.

Evaluating Changes in Soil Organic Matter with Climate Using CENTURY in England and Wales.

Soil organic C (SOC) dynamics are complex, and models have been developed for predicting future changes, validated using only individual site data. In this study, we used the CENTURY model to predict changes in SOC between 1978 and 2000 using input weather data for 1978 to 2000 from the UK Meteorological Office and soil property input data derived from the National Soil Inventory (NSI). The predicted changes in SOC from the model simulation were validated using the resampled NSI data for the period 1994 to 2000. The modeling results indicate that CENTURY gave unacceptable predictions of change for three specific soil types. When these were omitted from the accuracy assessment, model predictions were statistically acceptable for all ecosystem types with model efficiency (ME) decreasing in the order: seminatural grassland (ME = 0.63) > woodland (ME = 0.27) > arable (ME = 0.08) > managed grassland (ME = 0.02). When comparing the overall measured rates of change, CENTURY correctly predicted the direction but underpredicted the magnitude of change. Once this utility was established, CENTURY was used to predict nation-level climate change-induced changes in SOC with the UKCIP02 (UK Climate Impacts Program of 2002) scenarios for the 2020s, 2050s, and 2080s, each of which comprise four emissions scenarios. The modeling predictions suggest that the predicted changes between scenarios were small. However, within that, the greatest decrease (of 1.54% SOC) will be in seminatural grassland under the high emissions scenario. The future predicted pattern of change in SOC is greater in managed grassland (reduction of 0.27-0.39% SOC) than arable land (reduction of 0.03-0.05% SOC).

Temperature constraints shaped the migration routes of mackerel (Scomber scombrus) in the Black Sea

Conventional narratives explain fish migrations in term of requirements (food, mates, habitats, etc.), with adequate temperatures being optional. Here, using the example of a (commercially extinct) stock of Black Sea mackerel (Scomber scombrus), we suggest that seasonal migrations are driven by seasonal temperature cycles. Therein, temperature acts as a constraint determining where the fish can be at any given time, and not a one of several factors which they would consider when choosing between alternative migration routes. Generalizing, we suggest that temperature should generally be an explicit part of hypotheses about the migratory behaviours of marine fishes. For illustration of what may occur when this is not the case, it is suggested that the non-consideration of temperature in a model of North Atlantic mackerel migration may have led, among the researchers concerned, to a sense of complacency with respect to the climate change-induced changes in the phenology of this fish in the North Atlantic, whose distribution and migration are misleadingly seen as “stochastic”.

Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands.

Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change-induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems.

The rapid climate change-caused dichotomy on subtropical evergreen broad-leaved forest in Yunnan: Reduction in habitat diversity and increase in species diversity

Yunnan's biodiversity is under considerable pressure and subtropical evergreen broad-leaved forests in this area have become increasingly fragmented through agriculture, logging, planting of economic plants, mining activities and changing environment. The aims of the study are to investigate climate change-induced changes of subtropical evergreen broad-leaved forests in Yunnan and identify areas of current species richness centers for conservation preparation. Stacked species distribution models were created to generate ensemble forecasting of species distributions, alpha diversity and beta diversity for Yunnan's subtropical evergreen broad-leaved forests in both current and future climate scenarios. Under stacked species distribution models in rapid climate changes scenarios, changes of water-energy dynamics may possibly reduce beta diversity and increase alpha diversity. This point provides insight for future conservation of evergreen broad-leaved forest in Yunnan, highlighting the need to fully consider the problem of vegetation homogenization caused by transformation of water-energy dynamics.

Estimation of the impact of climate change-induced extreme precipitation events on floods

Abstract In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981–2010 period, 20 events of the basin’s most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa.

BackgroundAfrica is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types.ResultsContinental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship.ConclusionObserved significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

Modelling the influence of climate change on the chemical concentrations in the Baltic Sea region with the POPCYCLING-Baltic model

The effect of projected future changes in temperature, wind speed, precipitation and particulate organic carbon on concentrations of persistent organic chemicals in the Baltic Sea regional environment is evaluated using the POPCYCLING-Baltic multimedia chemical fate model. Steady-state concentrations of hypothetical perfectly persistent chemicals with property combinations that encompass the entire plausible range for non-ionizing organic substances are modelled under two alternative climate change scenarios (IPCC A2 and B2) and compared to a baseline climate scenario. The contributions of individual climate parameters are deduced in model experiments in which only one of the four parameters is changed from the baseline scenario. Of the four selected climate parameters, temperature is the most influential, and wind speed is least. Chemical concentrations in the Baltic region are projected to change by factors of up to 3.0 compared to the baseline climate scenario. For chemicals with property combinations similar to legacy persistent organic pollutants listed by the Stockholm Convention, modelled concentration ratios between two climate change scenarios and the baseline scenario range from factors of 0.5 to 2.0. This study is a first step toward quantitatively assessing climate change-induced changes in the environmental concentrations of persistent organic chemicals in the Baltic Sea region.