Abstract:In this study, the interferometric coherence calculated from 12-day Sentinel-1 image pairs was analysed in relation to mowing events on agricultural grasslands. Results showed that after a mowing event, median VH (vertical transmit, horizontal receive) and VV (vertical transmit, vertical receive) polarisation coherence values were statistically significantly higher than those from before the event. The shorter the time interval after the mowing event and the first interferometric acquisition, the higher the coherence. The coherence tended to stay higher, even 24 to 36 days after a mowing event. Precipitation caused the coherence to decrease, impeding the detection of a mowing event. Given the three analysed acquisition geometries, it was concluded that afternoon acquisitions and steeper incidence angles were more useful in the context of this study. In the case of morning acquisitions, dew might have caused a decrease of coherence for mowed and unmowed grasslands. Additionally, an increase of coherence after a mowing event was not evident during the rapid growth phase, due to the 12-day separation between the interferometric acquisitions. In future studies, six-day pairs utilising Sentinel-1A and 1B acquisitions should be considered.

Particulate matter (PM) is the major air pollution problem with health impacts in Estonia. The prevailing sources of particles are traffic and local heating. In this study, we quantified the health effects of PM in neighbourhoods of five main cities with a health impact assessment (HIA) approach that uses information on exposure, baseline mortality/morbidity and exposure-response relationships from previous epidemiological studies. The exposure was defined as modelled PM 2.5 annual levels and daily averages of PM 10 (monitoring data in Tallinn and Kohtla-Järve and modelled levels in Tartu, Narva and Pärnu). The modelled results were validated with data from monitoring stations and additional measuring programmes. The annual average concentration of PM 2.5 in the neighbourhoods studied varied from 7.6 to 23.6 μg m −3 . The analysis indicated that the exposure above natural background corresponds to 462 [95% confidence interval (CI) 120-815] premature deaths, resulting in 6,034 (95% CI 1,583-10,309) years of life lost per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.63 (95% CI 0.16-1.08) years. In the polluted city centres, this average decrease may reach >1 year and in Pärnu, it may reach 0.95 year. However, in the least polluted neighbourhood, the decrease of life expectancy was only 0.17 years. In addition, 231 (95% CI 145-306) respiratory and 338 (95% CI 205-454) cardiovascular hospitalisations per year could be expected. The majority of the external costs are related to the long-term effects on mortality and amount to €270 (95% CI 190-350) million annually. In comparison, the costs of hospitalisations contribute just €1.1 (95% CI 0.6-1.6) million. The main differences in health impacts were mostly driven by differences in the pollution sources, the magnitude of such sources and distribution patterns in the atmosphere. The smallest health effects, with the exception of the green residential areas, were observed in the industrial cities Kohtla-Järve and Narva (due to the small share contributed by local residential heating and relatively little car traffic). However, it is questionable whether the mass of fine particles is the best indicator of air pollution risk in such areas.

Short temporal baseline regular Synthetic Aperture Radar (SAR) interferometry is a tool well suited for wide area monitoring of agricultural activities, urgently needed in European Union Common Agricultural Policy (CAP) enforcement. In this study, we demonstrate and describe in detail, how mowing and ploughing events can be identified from Sentinel-1 6-day interferometric coherence time series. The study is based on a large dataset of 386 dual polarimetric Sentinel-1 VV/VH SAR and 351 Sentinel-2 optical images, and nearly 2000 documented mowing and ploughing events on more than 1000 parcels (average 10.6 ha, smallest 0.6 ha, largest 108.5 ha). Statistical analysis revealed that mowing and ploughing cause coherence to increase when compared to values before an event. In the case of mowing, the coherence increased from 0.18 to 0.35, while Sentinel-2 NDVI (indicating the amount of green chlorophyll containing biomass) at the same time decreased from 0.75 to 0.5. For mowing, there was virtually no difference between the polarisations. After ploughing, VV-coherence grew up to 0.65 and VH-coherence to 0.45, while NDVI was around 0.2 at the same time. Before ploughing, both coherence and NDVI values were very variable, determined by the agricultural management practices of the parcel. Results presented here can be used for planning further studies and developing mowing and ploughing detection algorithms based on Sentinel-1 data. Besides CAP enforcement, the results are also useful for food security and land use change detection applications.

BackgroundHealth impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.MethodsTallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390 000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM10 or PM2.5 levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6–11%) per 10 μg/m3 increase of annual mean PM2.5 concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62–1.67%) and 0.73% (95% CI 0.47–0.93%) per 10 μg/m3 increase of PM10. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY).ResultsThe annual population-weighted-modeled exposure to locally emitted PM2.5 in Tallinn was 11.6 μg/m3. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17–1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43–104) respiratory and 204 (95% CI 131–260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average €150 (95% CI 40–260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small €0.3 (95% CI 0.2–0.4) million.ConclusionSectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.

Climate change is expected to increase to extreme temperatures and lead to more intense formation of near-surface ozone. Higher temperatures can cause heat stress and ozone is a highly oxidative pollutant; both increase cardiorespiratory mortality. Using greenhouse gas and ozone precursor emission scenarios, global and regional climate and chemistry-transport models, epidemiological data, and population projections, we projected ozone-and heat-related health risks under a changing climate. European near-surface temperature was modelled with the regional climate model (RCA4), forced by the greenhouse gas emission scenario RCP4.5 and the global climate model EC-EARTH, and near-surface ozone was modelled with the Multi-scale Atmospheric Transport and Chemistry (MATCH) model. Two periods were compared: recent climate in 1991-2000 and future climate in 2046-2055, projecting around a 2°increase in global temperatures by that time. Projections of premature mortality considered future climate, future population, and future emissions separately and jointly to understand the relative importance of their contributions. Ozone currently causes 55 000 premature deaths annually in Europe due to long-term exposure, including a proportion of the estimated 26 000 deaths per year due to short-term exposures. When only taking into account the impact of a changing climate, up to an 11% increase in ozone-associated mortality is expected in some countries in Central and Southern Europe in 2050. However, projected decreases in ozone precursor emissions are expected to result in a decrease in ozone-related mortality (−30% as EU average). Due to aging and increasingly susceptible populations, the decrease in 2050 would be smaller, up to −24%. During summer months, ozone risks could combine with increasing temperatures, especially during the hottest periods and in densely populated urban areas. While the heat burden is currently of the same order of magnitude as ozone, due to increasing temperatures and decreasing ozone precursor emissions, heat-related mortality could be twice as large as ozone-related mortality in 2050.