European Pollutant Release Research Articles

Toxic pollution and labour markets: uncovering Europe’s left-behind places

AbstractThis paper looks at the co-evolution of toxic industrial pollution and economic deprivation by means of spillovers from the plant’s production activities. Geolocalised facility-level data from the European Pollutant Release and Transfer Register (E-PRTR) are used to calculate annual chemical-specific pollution, weighted by its toxicity. We combine the latter with regional data on employment, wages, and demographics sourced from Cambridge Econometrics, covering more than 1200 NUTS‑3 regions in 15 countries, over the period 2007–2018. We employ quantile regressions to detect the heterogeneity across regions and understand the specificities of the 10th and 25th percentiles. Our first contribution consists in giving a novel and comprehensive account of the geography of toxic pollution in Europe, both at facility and regional level, disaggregated by sectors. Second, we regress toxic pollution (intensity effect) and pollutant concentration (composition effect) on labour market dimensions of left-behind places. Our results point to the existence of economic dependence on noxious industrialisation in left-behind places. In addition, whenever environmental efficiency-enhancing production technologies are adopted we observe associated labour-saving effects in industrial employment, but positive regional spillovers. Through the lens of economic geography, our results call for a new political economy of left-behind places within the realm of sustainable development.

Managerial and Financial Barriers to the Green Transition

Using data on 10,776 firms across 22 emerging markets, we show that both credit constraints and weak green management hold back corporate investment in green technologies embodied in new machinery, equipment, and vehicles. In contrast, investment in measures to explicitly reduce emissions and other pollution is mainly determined by the quality of a firm’s green management and less so by binding credit constraints. Data from the European Pollutant Release and Transfer Register reveal the environmental impact of these organizational constraints. In areas where more firms are credit constrained and weakly managed, industrial facilities systematically emit more CO2 and pollutants. A counterfactual analysis shows that credit constraints and weak management have respectively kept CO2 emissions 4.5% and 2.3% above the levels that would have prevailed without such constraints. This is further corroborated by our finding that in localities where banks had to deleverage more due to the global financial crisis, carbon emissions by industrial facilities remained 5.6% higher a decade later. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.00772 .

Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Abstract. Coal mining accounts for ∼12 % of the total anthropogenic methane (CH4) emissions worldwide. The Upper Silesian Coal Basin (USCB), Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coal bed CH4 emissions into the atmosphere are poorly characterized. As part of the carbon dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May–June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speed, and surface wind direction. We used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2=0.7–0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified. As an alternative, we have developed three upscaling approaches, i.e., by scaling the European Pollutant Release and Transfer Register (E-PRTR) annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate, which are derived from the hourly emission inventory. These estimates are in the range of 256–383 kt CH4 yr−1 for the inverse Gaussian (IG) approach and 228–339 kt CH4 yr−1 for the mass balance (MB) approach. We have also estimated the total CO2 emissions from coal mining ventilation shafts based on the observed ratio of CH4/CO2 and found that the estimated regional CO2 emissions are not a major source of CO2 in the USCB. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.

Constraining industrial ammonia emissions using hyperspectral infrared imaging

Atmospheric emissions of reactive nitrogen in the form of nitrogen dioxide (NO2) and ammonia (NH3) worsen air quality and upon deposition, dramatically affect the environment. Recent infrared satellite measurements have revealed that NH3 emitted by industries are an important and underestimated emission source. Yet, to assess these emissions, current satellite sounders are severely limited by their spatial resolution. In this paper, we analyse measurement data recorded in a series of imaging surveys that were conducted over industries in the Greater Berlin area (Germany). On board the aircraft were the Telops Hyper-Cam LW, targeting NH3 measurements in the longwave infrared at a resolution of 4 m and the SWING+ spectrometer targeting NO2 measurements in the UV–Vis at a resolution of 180 m.Two flights were carried out over German’s largest production facility of synthetic NH3, urea and other fertilizers. In both cases, a large NH3 plume was observed originating from the factory. Using a Gaussian plume model to take into account plume rise and dispersion, coupled with well-established radiative transfer and inverse methods, we retrieve vertical column densities. From these, we calculate NH3 emission fluxes using the integrated mass enhancement and cross-sectional flux methods, yielding consistent emissions of the order of 2200 t yr−1 for both flights, assuming constant fluxes across the year. These estimates are about five times larger than those reported in the European Pollutant Release and Transfer Register (E-PRTR) for this plant. In the second campaign, a co-emitted NO2 plume was measured, likely related to the production of nitric acid at the plant.A third flight was carried out over an area comprising the cities of Staßfurt and Bernburg. Several small NH3 plumes were seen, one over a production facility of mineral wool insulation, one over a sugar factory and two over the soda ash plants in Staßfurt and Bernburg. A fifth and much larger plume was seen to originate from the sedimentation basins associated with the soda ash plant in Staßfurt, indicating rapid volatilization of ammonium rich effluents. We use the different measurement campaigns to simulate measurements of Nitrosat, a potential future satellite sounder dedicated to the sounding of reactive nitrogen at a resolution of 500 m. We demonstrate that such measurements would allow accurately constraining emissions in a single overpass, overcoming a number of important drawbacks of current satellite sounders.

SENTIERI Project: air pollution and health impact of population living in industrial areas in Italy

to estimate the impact of PM2.5 and PM10 in the Italian industrial areas included in the SENTIERI project characterized by industrial plants with combustion processes deriving from point emissions. using satellite data, the Population Weighted Exposure (PWE) to PM2.5 and PM10 for 2011 and 2015 was estimated. The concentration-response functions available were used to estimate the number of premature deaths attributable to exposure to industrial emissions. The counterfactual levels recommended by the new WHO Air Quality Guidelines were used. for the selection of industrial plants, the European database on emissions of the European Pollutant Release and Transfer Register was used. Residents in areas of 1 km x 1 km and 4 km x 4 km around the selected industrial plants were considered. the number of premature deaths from non-accidental causes, cardiovascular and respiratory diseases, and lung cancer was estimated. residents were exposed to PM2.5 values of 17.3 µg/m3 (Northern Italy: 23.3) and to 24.3 µg/m3 (Northern Italy: 30.3) of PM10. PWE for both pollutants tends to increase as the size of the area under study is reduced and it is generally higher everywhere in 2011 than in 2015, with values that are always higher than the average (overall) in the Norther Italy. In 2011, 1,709 (IC95% 1,309-1,903) and 1,611 (IC95% 1,225-2,353) non accidental premature deaths were estimated attributable to PM2.5 and PM10, respectively, in residents close to the industrial plants (1 km x 1 km). Deaths attributable to exposure to PM2.5 and PM10 tend to follow a North-Central-South&Islands gradient for all observed causes and for both years of analysis. although exposure assessment of the population by using random-forest model does not allow to disentangle the contribution of the industrial component, the results of the study are suggestive of an impact on health from PM exposure in the industrial areas considered, with a greater impact in the vicinity of the plants, recommending the implementation of urgent impact reduction actions.

Environmental ranking of European industrial facilities by toxicity and global warming potentials

We present a methodology to develop the integrated toxicity and climate change risk assessment of Europe based facilities, industries and regions. There is an increasingly important need for large scale sustainability measurement solutions for company reporting with high granularity. In this paper we measure key aspects of Sustainable Development Goals in terms of human, cancer and non-cancer toxicity, ecotoxicity together with global warming impact potentials from point source pollutant releases of more than 10,000 companies and their 33,000 facilities in Europe from 2001 to 2017, by using the European Pollutant Release and Transfer Register. For our assessment, we deploy a scientific consensus model, USEtox for characterizing human and ecotoxicological impacts of chemicals and the global warming potential values from the Intergovernmental Panel on Climate Change. We discuss water and air emissions of dozens of pollutants in urban, rural, coastal and inland areas. Companies in the electricity production sector are estimated to have the largest human toxicity impact potential (46% of total) and the largest global warming impact potential (50%), while companies in the sewerage sector have the largest ecotoxicity impact potential (50%). In the overall economy, the correlation between facilities’ global warming and toxicity impact potentials is positive, however, not very strong. Therefore, we argue that carbon footprint of industrial organizations can be only used as a climate change risk indicator, but not as an overall environmental performance indicator. We confirm impact potentials of major pollutants in previous research papers (Hg accounting for 76% of the total human toxicity and Zn accounting for 68% of total ecotoxicity), although we draw the attention to the limitations of USEtox in case of metals. From 2001 to 2017 total human toxicity dropped by 28%, although the downward trend reversed in 2016. Ecotoxicity and global warming impact potentials remained unchanged in the same period. Finally, we show that the European pollutant release monitoring data quality could be further improved, as only three quarters of the toxic releases are measured in the Member States of the European Union, and a high share of toxic pollutant releases are only estimated in some countries. Of the measured or calculated toxic releases, only one third is reported according to the most robust CEN/ISO standards and about one fifth according to the least preferred other methods, like engineering judgements.

Quantifying CH4 emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method

Abstract. Intensive coal mining activities in the Upper Silesian Coal Basin (USCB) in southern Poland are resulting in large amounts of methane (CH4) emissions. Annual CH4 emissions reached 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hotspot in Europe, it is of importance to investigate its emission sources and make accurate emission estimates. In this study, we use satellite-based total column-averaged dry-air mole fraction of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI). In addition, the high-resolution model forecasts, XCH4 and TXCH4, from the Copernicus Atmosphere Monitoring Service (CAMS) are used to estimate the CH4 emission rate averaged over 3 years (November 2017–December 2020) in the USCB region (49.3–50.8∘ N and 18–20∘ E). The wind-assigned anomaly method is first validated using the CAMS forecast data (XCH4 and TXCH4), showing a good agreement with the CAMS GLOBal ANThropogenic emission (CAMS-GLOB-ANT) inventory. It indicates that the wind-assigned method works well. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI + IASI TXCH4 by using the Carbon dioxide and Methane (CoMet) inventory derived for the year 2018. The calculated averaged total CH4 emissions over the USCB region is about 496 kt yr−1 (5.9×1026 molec. s−1) for TROPOMI XCH4 and 437 kt yr−1 (5.2×1026 molec. s−1) for TROPOMI + IASI TXCH4. These values are very close to the ones given in the E-PRTR inventory (448 kt yr−1) and the ones in the CoMet inventory (555 kt yr−1), and are thus in agreement with these inventories. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region are of secondary importance. Uncertainties from different error sources (background removal and noise in the data, vertical wind shear, wind field segmentation, and angle of the emission cone) are approximately 14.8 % for TROPOMI XCH4 and 11.4 % for TROPOMI + IASI TXCH4. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions.

Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network

Abstract. Given its abundant coal mining activities, the Upper Silesian Coal Basin (USCB) in southern Poland is one of the largest sources of anthropogenic methane (CH4) emissions in Europe. Here, we report on CH4 emission estimates for coal mine ventilation facilities in the USCB. Our estimates are driven by pairwise upwind–downwind observations of the column-average dry-air mole fractions of CH4 (XCH4) by a network of four portable, ground-based, sun-viewing Fourier transform spectrometers of the type EM27/SUN operated during the CoMet campaign in May–June 2018. The EM27/SUN instruments were deployed in the four cardinal directions around the USCB approximately 50 km from the center of the basin. We report on six case studies for which we inferred emissions by evaluating the mismatch between the observed downwind enhancements and simulations based on trajectory calculations releasing particles out of the ventilation shafts using the Lagrangian particle dispersion model FLEXPART. The latter was driven by wind fields calculated by WRF (Weather Research and Forecasting model) under assimilation of vertical wind profile measurements of three co-deployed wind lidars. For emission estimation, we use a Phillips–Tikhonov regularization scheme with the L-curve criterion. Diagnosed by the emissions averaging kernels, we find that, depending on the catchment area of the downwind measurements, our ad hoc network can resolve individual facilities or groups of ventilation facilities but that inspecting the emissions averaging kernels is essential to detect correlated estimates. Generally, our instantaneous emission estimates range between 80 and 133 kt CH4 a−1 for the southeastern part of the USCB and between 414 and 790 kt CH4 a−1 for various larger parts of the basin, suggesting higher emissions than expected from the annual emissions reported by the E-PRTR (European Pollutant Release and Transfer Register). Uncertainties range between 23 % and 36 %, dominated by the error contribution from uncertain wind fields.

Residential proximity to industrial pollution and mammographic density

BackgroundMammographic density (MD), expressed as percentage of fibroglandular breast tissue, is an important risk factor for breast cancer. Our objective is to investigate the relationship between MD and residential proximity to pollutant industries in premenopausal Spanish women. MethodsA cross-sectional study was carried out in a sample of 1225 women extracted from the DDM-Madrid study. Multiple linear regression models were used to assess the association of MD percentage (and their 95% confidence intervals (95%CIs)) and proximity (between 1 km and 3 km) to industries included in the European Pollutant Release and Transfer Register. ResultsAlthough no association was found between MD and distance to all industries as a whole, several industrial sectors showed significant association for some distances: “surface treatment of metals and plastic” (β = 4.98, 95%CI = (0.85; 9.12) at ≤1.5 km, and β = 3.00, 95%CI = (0.26; 5.73) at ≤2.5 km), “organic chemical industry” (β = 6.73, 95%CI = (0.50; 12.97) at ≤1.5 km), “pharmaceutical products” (β = 4.14, 95%CI = (0.58; 7.70) at ≤2 km; β = 3.55, 95%CI = (0.49; 6.60) at ≤2.5 km; and β = 3.11, 95%CI = (0.20; 6.01) at ≤3 km), and “urban waste-water treatment plants” (β = 8.06, 95%CI = (0.82; 15.30) at ≤1 km; β = 5.28; 95%CI = (0.49; 10.06) at ≤1.5 km; β = 4.30, 95%CI = (0.03; 8.57) at ≤2 km; β = 5.26, 95%CI = (1.83; 8.68) at ≤2.5 km; and β = 3.19, 95%CI = (0.46; 5.92) at ≤3 km). Moreover, significant increased MD was observed in women close to industries releasing specific pollutants: ammonia (β = 4.55, 95%CI = (0.26; 8.83) at ≤1.5 km; and β = 3.81, 95%CI = (0.49; 7.14) at ≤2 km), dichloromethane (β = 3.86, 95%CI = (0.00; 7.71) at ≤2 km), ethylbenzene (β = 8.96, 95%CI = (0.57; 17.35) at ≤3 km), and phenols (β = 2.60, 95%CI = (0.21; 5.00) at ≤2.5 km). ConclusionsOur results suggest no statistically significant relationship between MD and proximity to industries as a whole, although we detected associations with various industrial sectors and some specific pollutants, which suggests that MD could have a mediating role in breast carcinogenesis.

Quantifying methane emissions from coal mining ventilation shafts using an unmanned aerial vehicle (UAV)-based active AirCore system

A large quantity of CH4 is emitted to the atmosphere via ventilation shafts of underground coal mines. According to the European Pollutant Release and Transfer Register (E-PRTR), hard coal mines in the Upper Silesia Coal Basin (USCB) are a strong contributor (447 kt CH4 in 2017) to the annual European CH4 emissions. However, atmospheric emissions of CH4 from coal mines are poorly characterized, as they are dispersed over large areas. As part of the Carbon Dioxide and CH4 Mission (CoMet) pre-campaign, a study of the USCB's regional CH4 emissions took place in August 2017. We flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 mole fractions downwind of a single coal mining ventilation shaft. Besides CH4, we also measured CO2, CO, atmospheric temperature, pressure, and relative humidity. Wind-speed and wind-direction measurements were made using a lightweight balloon-borne radiosonde. Fifteen UAV flights were performed flying perpendicular to the wind direction at several altitude levels, to effectively build a ‘curtain’ of CH4 mole fractions in a two-dimensional plane at a distance between 150 and 350 m downwind of a single ventilation shaft. Furthermore, we have developed an inverse Gaussian approach for quantifying CH4 emissions from a point source using the UAV-based observations, and have applied it as well as the mass balance approach to both simulated data and actual flight data to quantify CH4 emissions. The simulated data experiments revealed the importance of having multiple transects at different altitudes, appropriate vertical spacing between the individual transects, and proper distance between the center height of the plume and the center flight transect. They also showed that the inverse Gaussian approach performed better than the mass balance approach. Our estimate of the CH4 emission rates from the sampled shaft ranges from 0.5 to 14.5 kt/year using a mass balance approach, and between 1.1 and 9.0 kt/year using an inverse Gaussian method. The average difference between the mass balance and the inverse Gaussian approach was 2.3 kt/year. Based on the observed correlation between CO2 and CH4 (R-squared > 0.69), the CO2 emissions from the shaft were estimated to be between 0.3 and 9.8 kt/year. This study demonstrates that the UAV-based active AirCore system provides an effective way of quantifying coal mining shaft emissions of CH4 and CO2.

Monte-Carlo modelling to demonstrate the influence of alternative flow reference techniques on annual mass emission uncertainty

Industrial emissions into the atmosphere are quantified by measuring the concentration and flow rate in a duct or stack prior to release. These measurements are combined to produce a mass emission which is reported to the European Pollutant Release and Transfer Register. These measurements have to be made according to standards to ensure that they are consistent and accurate. Uncertainty limits are set in relevant EU legislation which must be adhered to. The standard for flow measurement, EN ISO 16911, is in two parts covering manual reference methods and automated measuring systems (AMS). The former outlines six validated methods for calibrating an AMS, while the later outlines the quality control system to be followed to meet the requirements of the legislation. However the standard does not provide consistent information on the impact of the different calibration methods on the uncertainty of the reported emissions. Here we model a system monitoring stack flow and pollutant concentration, including quality control procedures in EN ISO 16911. Several alternative reference methods are modelled to compare the effects of using these different techniques for calibration on the uncertainty of reported annual mass emissions. In a low uncertainty regime the L- and S-type Pitot provide the best performance for both constant and variable flows, however in higher uncertainty regimes all the techniques led to a bias that would lead to misreporting of emissions. Uncertainty information on the techniques is not equally characterised, however, this information represents the best current knowledge of these uncertainties in the emissions community and so the comparisons reported here are all made with the best knowledge available.

Application of North European characterisation factors, population density and distance-to-coast grid data for refreshing the Swedish human toxicity and ecotoxicity footprint analysis

Here, we develop further the national chemical footprint assessment methods using Sweden as an example to enhance the precision of calculations. First, we integrate grid data on population density and distance-to-seacoast into the analytical framework to better match the European Pollutant Release and Transfer Register on the sub-compartment level with USEtox toxicity characterisation factors. Second, we use the latest USEtox 2.12 model version and its more punctual North European characterisation factors. Third, we conduct trend and geographic analysis and rank Swedish facilities in terms of toxicity potential. We show that total human toxicity potential in Sweden was smaller than previously estimated when using the North European USEtox landscape settings and sloped downwards over time. We confirm toxicity potential of major pollutants in previous research papers (Zn, Hg, Pb, Ni) and find that Hg’s relative human toxicity potential in a longer period can be larger than previously estimated on shorter periods. Human toxicity is estimated to be mostly non-cancer type in Sweden. Results are largely invariant to the choice of air sub-compartments. Companies in the metals manufacturing sector are estimated to have the largest human toxicity potential in Sweden in the period between 2001 and 2017 and companies in the paper manufacturing industry have the largest ecotoxicity potential.

Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

Estimating Upper Silesian coal mine methane emissions from airborne in situ observations and dispersion modeling

Abstract. Abundant mining and industrial activities located in the Upper Silesian Coal Basin (USCB) lead to large emissions of the potent greenhouse gas (GHG) methane (CH4). The strong localization of CH4 emitters (mostly confined to known coal mine ventilation shafts) and the large emissions of 448 and 720 kt CH4 yr−1 reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) and the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2), respectively, make the USCB a prime research target for validating and improving CH4 flux estimation techniques. High-precision observations of this GHG were made downwind of local (e.g., single facilities) to regional-scale (e.g., agglomerations) sources in the context of the CoMet 1.0 campaign in early summer 2018. A quantum cascade–interband cascade laser (QCL–ICL)-based spectrometer adapted for airborne research was deployed aboard the German Aerospace Center (DLR) Cessna 208B to sample the planetary boundary layer (PBL) in situ. Regional CH4 emission estimates for the USCB are derived using a model approach including assimilated wind soundings from three ground-based Doppler lidars. Although retrieving estimates for individual emitters is difficult using only single flights due to sparse data availability, the combination of two flights allows for exploiting different meteorological conditions (analogous to a sparse tomography algorithm) to establish confidence on facility-level estimates. Emission rates from individual sources not only are needed for unambiguous comparisons between bottom-up and top-down inventories but also become indispensable if (independently verifiable) sanctions are to be imposed on individual companies emitting GHGs. An uncertainty analysis is presented for both the regional-scale and facility-level emission estimates. We find instantaneous coal mine emission estimates of 451/423 ± 77/79 kt CH4 yr−1 for the morning/afternoon flight of 6 June 2018. The derived fuel-exploitation emission rates coincide (±6 %) with annual-average inventorial data from E-PRTR 2017 although they are distinctly lower (−28 %/−32 %) than values reported in EDGAR v4.3.2. Discrepancies in available emission inventories could potentially be narrowed down with sufficient observations using the method described herein to bridge the gap between instantaneous emission estimates and yearly averaged inventories.

Managerial and Financial Barriers to the Net Zero Transition

We use data on 11,233 firms across 22 emerging markets to analyze how credit constraints and low-quality firm management inhibit corporate investment in green technologies. For identification we exploit quasi-exogenous variation in local credit conditions and in exposure to weather shocks. Our results suggest that both financial frictions and managerial constraints slow down firm investment in more energy efficient and less polluting technologies. Complementary analysis of data from the European Pollutant Release and Transfer Register (E-PRTR) corroborates some of this evidence by revealing that in areas where banks deleveraged more after the global financial crisis, industrial facilities reduced their carbon emissions by less. On aggregate this kept local emissions 15% above the level they would have been in the absence of financial frictions. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.)

Managerial and Financial Barriers to the Net-Zero Transition

We use data on 11,233 firms across 22 emerging markets to analyze how credit constraints and low-quality firm management inhibit corporate investment in green technologies. For identification we exploit quasi-exogenous variation in local credit conditions and in exposure to weather shocks. Our results suggest that both financial frictions and managerial constraints slow down frim investment in more energy efficient and less polluting technologies. Complementary analysis of data from the European Pollutant Release and Transfer Register (E-PRTR) corroborates some of this evidence by revealing that in areas where banks deleveraged more after the global - financial crisis, industrial facilities reduced their carbon emissions by less. On aggregate this kept local emissions 15% above the level they would have been in the absence of financial frictions.

Tensions in the energy transition: Swedish and Finnish company perspectives on bioenergy with carbon capture and storage

Sweden and Finland have national goals to reach net negative greenhouse gas emissions before mid-century. Achieving these ambitious goals could employ negative emission technologies, such as bioenergy with carbon capture and storage, but it is unclear how this technology could be realized in an energy transition. Sweden and Finland stand out for having a large share of substantial point source emissions of biogenic carbon dioxide, in the production of pulp, heat and power. In the European Pollutant Release and Transfer Register, Sweden and Finland reported 64% and 51% biogenic emissions, respectively, in facilities emitting over 100 kt of carbon dioxide in 2017, while the corresponding collective figure for all European states in the database is 6%. This qualitative study highlights company actors’ perspectives on bioenergy with carbon capture and storage within a Nordic regional context and explores their perspective on emerging tensions in the energy transition. Semi-structured interviews were conducted with 20 of the 24 companies with the largest point sources of biogenic emissions. The results are framed around four emerging tensions regarding bioenergy with carbon capture and storage from companies’ perspectives in this study: (1) absence of reliable long-term policies; (2) limits to companies’ climate change responsibility; (3) technical trade-offs of carbon capture; and (4) lack of customer demands for negative emissions. According to most of the companies, it is technically feasible to capture carbon dioxide, but it could be a challenge to determine who is responsible to create a financially viable business case, to enact supporting policies, and to build transport and storage infrastructure. Company representatives argue that they already contribute to a sustainable society, therefore bioenergy with carbon capture and storage is not their priority without government collaboration. However, they are willing to contribute more and could have an increasing role towards an energy transition in an international context.

Use of non-health EU databases for health surveillance. En-risk application

Abstract Background To combine health information and environmental health determinants is key, for epidemiological monitoring and health risk studies but its integration represents a challenge that requires specific expertise. An example of a potentially useful source of significant environmental data relevant for health is the European Pollutant Release and Transfer Register (E-PRTR), which allows estimating exposure to industrial pollution. Our aim was to develop an easy-to-use tool that allows to perform a screening suggesting the presence/absence of excess risk of a disease linked to residential proximity to industrial pollution. Methods En-risk: java interactive tool was developed to merge E-PRTR information and municipal mortality/morbidity data, to perform an exploratory spatial analysis of association between them by type of industrial facility using distance as proxy of exposure. The application needs cartography of the country and a database of the annual observed deaths (mortality) or cases (morbidity) and population broken down by age groups and sex per municipality. With this it calculates the expected number of deaths, the distance from the municipal centroids to the industrial location (classifying municipalities as exposed or not exposed), and perform the statistical analyses. Municipal lung cancer deaths (2005-2009) in Spain provided by the National Institute of Statistics were analyzed with this application as an example. Results En-risk gives a table of Relative Risk of mortality/morbidity due to exposure to industrial pollution by industrial sector and sex. The analysis in lung cancer deaths showed an excess of mortality associated to proximity to several industrial sectors. Conclusions En-risk facilitates the study of the relationship between industrial pollution and health around Europe. It can be used by public health services to identify health problems.

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Industrial symbiosis involves creating integrated cycles of by-products and waste between networks of industrial actors in order to maximize economic value, while at the same time minimizing environmental strain. In such a network, the global environmental strain is no longer equal to the sum of the environmental strain of the individual actors, but it is dependent on how well the network performs as a whole. The development of methods to understand, manage or optimize such networks remains an open issue. In this paper we put forward a simulation model of by-product flow between industrial actors. The goal is to introduce a method for modelling symbiotic exchanges from a macro perspective. The model takes into account the effect of two main mechanisms on a multi-objective optimization of symbiotic processes. First it allows us to study the effect of geographical properties of the economic system, said differently, where actors are divided in space. Second, it allows us to study the effect of clustering complementary actors together as a function of distance, by means of a spatial correlation between the actors’ by-products. Our simulations unveil patterns that are relevant for macro-level policy. First, our results show that the geographical properties are an important factor for the macro performance of symbiotic processes. Second, spatial correlations, which can be interpreted as planned clusters such as Eco-industrial parks, can lead to a very effective macro performance, but only if these are strictly implemented. Finally, we provide a proof of concept by comparing the model to real world data from the European Pollutant Release and Transfer Register database using georeferencing of the companies in the dataset. This work opens up research opportunities in interactive data-driven models and platforms to support real-world implementation of industrial symbiosis.

Banking on the Environment? Financial Frictions, Firm Management, and Green Investments

We use data on 11,233 firms across 22 emerging markets to analyse how credit constraints and low-quality firm management inhibit corporate investment in green technologies. For identification, we exploit quasi-exogenous variation in local credit conditions and in exposure to weather shocks. Our results suggest that both financial frictions and managerial constraints slow down firm investment in more energy efficient and less polluting technologies. Complementary analysis of data from the European Pollutant Release and Transfer Register (E-PRTR) corroborates some of this evidence by revealing that in areas where banks deleveraged more after the global financial crisis, industrial facilities reduced their carbon emissions by less. On aggregate this kept local emissions 15% above the level they would have been in the absence of financial frictions.