Effect of climate change on air quality

Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m^?3 over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.     

Climate change: potential impact on plant diseases

Global climate has changed since pre-industrial times. Atmospheric CO(2), a major greenhouse gas, has increased by nearly 30% and temperature has risen by 0.3 to 0.6 degrees C. The intergovernmental panel on climate change predicts that with the current emission scenario, global mean temperature would rise between 0.9 and 3.5 degrees C by the year 2100. There are, however, many uncertainties that influence these predictions. Despite the significance of weather on plant diseases, comprehensive analysis of how climate change will influence plant diseases that impact primary production in agricultural systems is presently unavailable. Evaluation of the limited literature in this area suggests that the most likely impact of climate change will be felt in three areas: in losses from plant diseases, in the efficacy of disease management strategies and in the geographical distribution of plant diseases. Climate change could have positive, negative or no impact on individual plant diseases. More research is needed to obtain base-line information on different disease systems. Most plant disease models use different climatic variables and operate at a different spatial and temporal scale than do the global climate models. Improvements in methodology are necessary to realistically assess disease impacts at a global scale.     

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.     

Climate change impacts on the leaching of a heavy metal contamination in a small lowland catchment

The Keersop catchment (43km(2)) in the south of The Netherlands has been contaminated by the emissions of four zinc ore smelters. The objective of this study was to assess the effects of future projected climate change on the hydrology and the leaching of heavy metals (i.e. Cd and Zn) in the catchment. The numerical, quasi-2D, unsaturated zone Soil Water Atmosphere Plant model was used with 100-year simulated daily time series of precipitation and potential evapotranspiration. The time series are representative of stationary climates for the periods 1961-1990 ("baseline") and 2071-2100 ("future"). The time series of future climate were obtained by downscaling the results of eight regional climate model (RCM) experiments, driven by the SRES A2 emissions scenario, using change factors for a series of climate statistics and applying them to stochastic weather generator models. The time series are characterized by increased precipitation in winter, less precipitation in summer, and higher air temperatures (between 2°C and 5°C) throughout the year. Future climate scenarios project higher evapotranspiration rates, more irrigation, less drainage, lower discharge rates and lower groundwater levels, due to increased evapotranspiration and a slowing down of the groundwater system. As a result, lower concentrations of Cd and Zn in surface water are projected. The reduced leaching of heavy metals, due to drying of the catchment, showed a positive impact on a limited aspect of surface water quality.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

Ecosystem Response to Climatic Change: The Importance of the Cold Season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Ecosystem response to climatic change: the importance of the cold season

Winter climate and snow cover are the important drivers of plant community development in polar regions. However, the impacts of changing winter climate and associated changes in snow regime have received much less attention than changes during summer. Here, we synthesize the results from studies on the impacts of extreme winter weather events on polar heathland and lichen communities. Dwarf shrubs, mosses and soil arthropods were negatively impacted by extreme warming events while lichens showed variable responses to changes in extreme winter weather events. Snow mould formation underneath the snow may contribute to spatial heterogeneity in plant growth, arthropod communities and carbon cycling. Winter snow cover and depth will drive the reported impacts of winter climate change and add to spatial patterns in vegetation heterogeneity. The challenges ahead lie in obtaining better predictions on the snow patterns across the landscape and how these will be altered due to winter climate change.     

Mycorrhizal mediation of plant response to atmospheric change: Air quality concepts and research considerations

The term 'global climate change' encompasses many physical and chemical changes in the atmosphere that have been induced by anthropogenic pollutants. Increases in concentrations of CO2 and CH4 enhance the 'greenhouse effect' of the atmosphere and may contribute to changes in temperature and precipitation patterns at the earth's surface. Nitrogen oxides and SO2 are phytotoxic and also react with other pollutants to produce other phytotoxins in the troposphere such as O3 and acidic substances. However, release of chlorofluorocarbons into the atmosphere may cause depletion of stratospheric O3, increasing the transmittance of ultraviolet-B (UV-B) radiation to the earth's surface. Increased intensities of UV-B could affect plants and enhance photochemical reactions that generate some phytotoxic pollutants. The role of mycorrhizae in plant responses to such stresses has received little attention. Although plans for several research programs have acknowledged the importance of drought tolerance and soil fertility in plant responses to atmospheric stresses, mycorrhizae are rarely targeted to receive specific investigation. Most vascular land plants form mycorrhizae, so the role of mycorrhizae in mediating plant responses to atmospheric change may be an important consideration in predicting effects of atmospheric changes on plants in managed and natural ecosystems.     

Long-term changes in elemental deposition at the earth's surface

The rate of deposition of elements at a point on the earth's surface can change, quite dramatically, even on relatively short time-scales, as a function of weather patterns. On a global scale volcanoes (and more rarely large meteors) can overwhelm steadier sources of trace elements. In recent centuries human activities have increased emissions to the atmosphere to a point where they are above those of natural sources for some of the rarer elements. On a longer time-scale climate change can also alter the deposition of elements, although such changes are often slower than those brought about through anthropogenic emissions. Changes in climate can also alter the distribution of deposition, but there are few studies estimating such changes. This paper uses estimates of the balance of natural and anthropogenic sources of a range of elements to examine the likely variation in deposition at the earth's surface. It particularly focuses on those elements regarded as toxic, whose concentrations seem likely to go on increasing in industrial areas.     

Extremes of Temperature, Oxygen and Blooms in the Baltic Sea in a Changing Climate

In the future, the Baltic Sea ecosystem will be impacted both by climate change and by riverine and atmospheric nutrient inputs. Multi-model ensemble simulations comprising one IPCC scenario (A1B), two global climate models, two regional climate models, and three Baltic Sea ecosystem models were performed to elucidate the combined effect of climate change and changes in nutrient inputs. This study focuses on the occurrence of extreme events in the projected future climate. Results suggest that the number of days favoring cyanobacteria blooms could increase, anoxic events may become more frequent and last longer, and salinity may tend to decrease. Nutrient load reductions following the Baltic Sea Action Plan can reduce the deterioration of oxygen conditions.     

Evaluation of the Meteo-France response in ETEX release 1

During ETEX Meteo-France applied part of its emergency response system for critical events developped in the framework of the World Meteorological Organization environmental emergency response program. The atmospheric transport model used to forecast the evolution of a passive tracer is an eulerian model called MEDIA. In real time this model is driven by meteorological data from ARPEGE, the operational numerical weather prediction model available at the Meteo-France operation center. The overall evaluation of the results show that the model can reproduce the cloud displacement, but there exists a stretching in the transport direction. In the ATMES-II phase, the results are closer to the observations when meteorological data from the European Center for Medium range Weather Forecast are used. A simulation using analyzed meteorological data from ARPEGE every 6 h slightly improve the results comparing with the real-time experiment. All the simulations we performed reveal that the quality of the atmospheric transport model is strongly dependent on the quality of the driving numerical weather prediction model.     

The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1–4°C and 1–5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$).

Implications:?Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1–5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

Measuring atmospheric composition change

Scientific findings from the last decades have clearly highlighted the need for a more comprehensive approach to atmospheric change processes. In fact, observation of atmospheric composition variables has been an important activity of atmospheric research that has developed instrumental tools (advanced analytical techniques) and platforms (instrumented passenger aircrafts, ground-based in situ and remote sensing stations, earth observation satellite instruments) providing essential information on the composition of the atmosphere. The variability of the atmospheric system and the extreme complexity of the atmospheric cycles for short-lived gaseous and aerosol species have led to the development of complex models to interpret observations, test our theoretical understanding of atmospheric chemistry and predict future atmospheric composition. The validation of numerical models requires accurate information concerning the variability of atmospheric composition for targeted species via comparison with observations and measurements.In this paper, we provide an overview of recent advances in instrumentation and methodologies for measuring atmospheric composition changes from space, aircraft and the surface as well as recent improvements in laboratory techniques that permitted scientific advance in the field of atmospheric chemistry. Emphasis is given to the most promising and innovative technologies that will become operational in the near future to improve knowledge of atmospheric composition. Our current observation capacity, however, is not satisfactory to understand and predict future atmospheric composition changes, in relation to predicted climate warming. Based on the limitation of the current European observing system, we address the major gaps in a second part of the paper to explain why further developments in current observation strategies are still needed to strengthen and optimise an observing system not only capable of responding to the requirements of atmospheric services but also to newly open scientific questions.     

Methods of investigating urban wind fields—physical models

For evaluation of environmental problems in urban areas, models are needed. Physical models and mathematical models are the tools of the trade. Both types of models have advantages and limitations. The emphasis here is on boundary layer wind tunnels, which are well suited for the study of many urban climate situations. The boundary layer flow along the floor of a meteorological wind tunnel is a real flow which approximately represents a scaled down version of the atmospheric boundary layer under conditions of neutral stratification. Therefore, important practical problems involving urban atmospheric conditions can be studied in such wind tunnels by means of geometrically similar models of the urban area. Such problems involve wind forces on structures, pedestrian comfort, and diffusion processes from point sources, such as chimneys, tunnel exhausts and gaseous spills, or from line sources, such as traffic lines. The investigation of these processes in a wind tunnel must be seen, however, as one link only in a chain of actions.     

Enhanced science–stakeholder communication to improve ecosystem model performances for climate change impact assessments

In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science–stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science–stakeholder communication. By this, we hope to stimulate a discussion among the science–stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models.     

A dynamic modelling approach for estimating critical loads of nitrogen based on plant community changes under a changing climate

A dynamic model of forest ecosystems was used to investigate the effects of climate change, atmospheric deposition and harvest intensity on 48 forest sites in Sweden (n = 16) and Switzerland (n = 32). The model was used to investigate the feasibility of deriving critical loads for nitrogen (N) deposition based on changes in plant community composition. The simulations show that climate and atmospheric deposition have comparably important effects on N mobilization in the soil, as climate triggers the release of organically bound nitrogen stored in the soil during the elevated deposition period. Climate has the most important effect on plant community composition, underlining the fact that this cannot be ignored in future simulations of vegetation dynamics. Harvest intensity has comparatively little effect on the plant community in the long term, while it may be detrimental in the short term following cutting. This study shows: that critical loads of N deposition can be estimated using the plant community as an indicator; that future climatic changes must be taken into account; and that the definition of the reference deposition is critical for the outcome of this estimate.     

Uncertainty requirements in radiative forcing of climate change

The continuing increase in atmospheric carbon dioxide (CO2) makes it essential that climate sensitivity, the equilibrium change in global mean surface temperature that would result from a given radiative forcing, be quantified with known uncertainty. Present estimates are quite uncertain, 3 +/- 1.5 K for doubling of CO2. Model studies examining climate response to forcing by greenhouse gases and aerosols exhibit large differences in sensitivities and imposed aerosol forcings that raise questions regarding claims of their having reproduced observed large-scale changes in surface temperature over the 20th century. Present uncertainty in forcing, caused largely by uncertainty in forcing by aerosols, precludes meaningful model evaluation by comparison with observed global temperature change or empirical determination of climate sensitivity. Uncertainty in aerosol forcing must be reduced at least three-fold for uncertainty in climate sensitivity to be meaningfully reduced and bounded.     

Elevated atmospheric CO2 concentration and temperature across an urban–rural transect

The heat island effect and the high use of fossil fuels in large city centers are well documented, but by how much fossil fuel consumption is elevating atmospheric CO₂ concentrations and whether elevations in both atmospheric CO₂ and air temperature from rural to urban areas are consistently different from year to year are less well known. Our aim was to record atmospheric CO₂ concentrations, air temperature and other environmental variables in an urban area and compare it to suburban and rural sites to see if urban sites are experiencing climates expected globally in the future with climate change. A transect was established from Baltimore city center (Urban site), to the outer suburbs of Baltimore (suburban site) and out to an organic farm (rural site). At each site a weather station was set-up to monitor environmental variables for 5 years. Atmospheric CO₂ was consistently and significantly increased on average by 66 ppm from the rural to the urban site over the 5 years of the study. Air temperature was also consistently and significantly higher at the urban site (14.8 °C) compared to the suburban (13.6 °C) and rural (12.7 °C) sites. Relative humidity was not different between sites whereas the vapor pressure deficit (VPD) was significantly higher at the urban site compared to the suburban and rural sites. An increase in nitrogen deposition at the rural site of 0.6% and 1.0% compared to the suburban and urban sites was small enough not to affect soil nitrogen content. Dense urban areas with large populations and high vehicular traffic have significantly different microclimates compared to outlying suburban and rural areas. The increases in atmospheric CO₂ and air temperature are similar to changes predicted in the short term with global climate change, therefore providing an environment suitable for studying future effects of climate change on terrestrial ecosystems.     

Modeling the effect of climate change on the distribution of threatened medicinal orchid Satyrium nepalense D. Don in India

It is vital to understand the distribution area of a threatened plant species for its better conservation and management planning. Satyrium nepalense (family: Orchidaceae) is a threatened terrestrial orchid species with valuable medicinal and nutritional properties. The survival of S. nepalense in wild conditions has been challenged by increasing global surface temperature. Hence, understanding the impact of climate change on its potential distribution is crucial to conserve and restore this species. In present study, Maxent species distribution modeling algorithm was used to simulate the current distribution of S. nepalense in India and predict the possible range shift in projected future climate scenarios. A set of 19 bioclimatic variables from WorldClim database were used to predict the potential suitable habitats in current climatic condition and four Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios by integrating five General Circulation Models (GCMs) for future distribution modeling of species for the years 2050 and 2070. Furthermore, change analysis was performed to identify the suitable habitat in current and future climate for delineating range expansion (gain), contraction (loss), and stable (no change) habitats of species. The Maxent model predicted that?~?2.38% of the geographical area in India is presently climatically suitable for S. nepalense. The key bioclimatic variables affecting the distribution of studied species were the mean temperature of warmest quarter, mean temperature of wettest quarter, precipitation of warmest quarter, and temperature seasonality. Under future climate change scenarios, the total suitable habitat of S. nepalense will increase slightly in the Himalayan region and likely to migrate towards northward, but in the Western Ghats region, the suitable areas will be lost severely. The net habitat loss under four RCP scenarios was estimated from 26 to 39% for the year 2050, which could further increase from 47 to 60% by the year 2070. The finding of the predictive Maxent modeling approach indicates that warming climates could significantly affect the potential habitats of S. nepalense and hence suitable conservation measures need to be taken to protect this threatened orchid species in wild conditions.