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2005
2012
2021
2014
2019
A short introduction to the GEOmon and EBAS databases at NILU, available for the CityZen project. NILU TR
2010
2013
2005
2020
2020
Urbanization presents numerous societal challenges and exacerbates environmental issues. It is crucial to comprehend the current state and future direction of cities to formulate strategies and actions that mitigate negative consequences while ensuring a prosperous future for citizens. This study presents a universally applicable method for selecting indicators to gauge urban environmental sustainability. It aims to aid in structuring thinking for understanding and implementing Sustainable Development Goals (SDGs) within urban settings, using Norway as a case study but with a clear potential for broader applications. To achieve this, a comprehensive literature survey was conducted to gain insight into how urban environmental sustainability is conceptualized and operationalized in Norway. This involved assessing the key environmental challenges, as well as the strategies and action plans associated with them. Standardized sustainable cities' indicators served as references, which were then tailored to the municipal level to address the identified environmental challenges specific to Norwegian cities. Furthermore, the study discussed the proposed indicators for tracking the progress and state of these specific environmental challenges. In doing so, it establishes a foundation for comprehending environmental issues and establishing connections between indicators and environmental strategies and action plans in the urban sustainability context. Importantly, the methodologies and indicators we have unveiled in this study are designed to be applicable to cities beyond Norway, offering a scalable and adaptable approach for evaluating environmental challenges internationally. This work proposes a novel approach for evaluating the status and trends of environmental challenges by employing targeted indicators. These indicators can be expanded to include social and economic dimensions, enabling decision-makers and stakeholders to prioritize actions towards urban sustainability.
Elsevier
2024
Citizen-operated low-cost air quality sensors (LCSs) have expanded air quality monitoring through community engagement. However, still challenges related to lack of semantic standards, data quality, and interoperability hinder their integration into official air quality assessments, management, and research. Here, we introduce FILTER, a geospatially scalable framework designed to unify, correct, and enhance the reliability of crowd-sourced PM2.5 data across various LCS networks. FILTER assesses data quality through five steps: range check, constant value detection, outlier detection, spatial correlation, and spatial similarity. Using official data, we modeled PM2.5 spatial correlation and similarity (Euclidean distance) as functions of geographic distance as benchmarks for evaluating whether LCS measurements are sufficiently correlated/consistent with neighbors. Our study suggests a −10 to 10 Median Absolute Deviation threshold for outlier flagging (360 h). We find higher PM2.5 spatial correlation in DJF compared to JJA across Europe while lower PM2.5 similarity in DJF compared to JJA. We observe seasonal variability in the maximum possible distance between sensors and reference stations for in-situ (remote) PM2.5 data correction, with optimal thresholds of ∼11.5 km (DJF), ∼12.7 km (MAM), ∼20 km (JJA), and ∼17 km (SON). The values implicitly reflect the spatial representativeness of stations. ±15 km relaxation for each season remains feasible when data loss is a concern. We demonstrate and validate FILTER's effectiveness using European-scale data originating from the two community-based monitoring networks, sensor.community and PurpleAir with QC-ed/corrected output including 37,085 locations and 521,115,762 hourly timestamps. Results facilitate uptake and adoption of crowd-sourced LCS data in regulatory applications.
Elsevier
2025
A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean
Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (∼ 10Wm−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.
2018
2014
2014
Ammonia (NH3) is one of the most important gases emitted from agricultural practices. It affects air quality and the overall climate and is in turn influenced by long-term climate trends as well as by short-term fluctuations in local and regional meteorology. Previous studies have established the capability of the Infrared Atmospheric Sounding Interferometer (IASI) series of instruments, aboard the Metop satellites, to measure ammonia from space since 2007. In this study, we explore the interactions between atmospheric ammonia, land and meteorological variability, and long-term climate trends in Europe. We investigate the emission potential (Γsoil) of ammonia from the soil, which describes the soil–atmosphere ammonia exchange. Γsoil is generally calculated in-field or in laboratory experiments; here, and for the first time, we investigate a method which assesses it remotely using satellite data, reanalysis data products, and model simulations.
We focus on ammonia emission potential in March 2011, which marks the start of growing season in Europe. Our results show that Γsoil ranges from 2 × 103 to 9.5 × 104 (dimensionless) in fertilized cropland, such as in the North European Plain, and is of the order of 10–102 in a non-fertilized soil (e.g., forest and grassland). These results agree with in-field measurements from the literature, suggesting that our method can be used in other seasons and regions in the world. However, some improvements are needed in the determination of mass transfer coefficient k (m s−1), which is a crucial parameter to derive Γsoil.
Using a climate model, we estimate the expected increase in ammonia columns by the end of the century based on the increase in skin temperature (Tskin), under two different climate scenarios. Ammonia columns are projected to increase by up to 50 %, particularly in eastern Europe, under the SSP2-4.5 scenario and might even double (increase of 100 %) under the SSP5-8.5 scenario. The increase in skin temperature is responsible for a formation of new hotspots of ammonia in Belarus, Ukraine, Hungary, Moldova, parts of Romania, and Switzerland.
2023
A rise in HFC-23 emissions from eastern Asia since 2015
Trifluoromethane (CHF3, HFC-23), one of the most potent greenhouse gases among hydrofluorocarbons (HFCs), is mainly emitted to the atmosphere as a by-product in the production of the ozone-depleting legacy refrigerant and chemical feedstock chlorodifluoromethane (CHClF2, HCFC-22). A recent study on atmospheric observation-based global HFC-23 emissions (top-down estimates) showed significant discrepancies over 2014–2017 between the increase in the observation-derived emissions and the 87 % emission reduction expected from capture and destruction processes of HFC-23 at HCFC-22 production facilities implemented by national phase-out plans (bottom-up emission estimates) (Stanley et al., 2020). However, the actual regions responsible for the increased emissions were not identified. Here, we estimate the regional top-down emissions of HFC-23 for eastern Asia based on in situ measurements at Gosan, South Korea, and show that the HFC-23 emissions from eastern China have increased from 5.0±0.4 Gg yr−1 in 2008 to 9.5±1.0 Gg yr−1 in 2019. The continuous rise since 2015 was contrary to the large emissions reduction reported under the Chinese hydrochlorofluorocarbons production phase-out management plan (HPPMP). The cumulative difference between top-down and bottom-up estimates for 2015–2019 in eastern China was Gg, which accounts for 47±11 % of the global mismatch. Our analysis based on HCFC-22 production information suggests the HFC-23 emissions rise in eastern China is more likely associated with known HCFC-22 production facilities rather than the existence of unreported, unknown HCFC-22 production, and thus observed discrepancies between top-down and bottom-up emissions could be attributed to unsuccessful factory-level HFC-23 abatement and inaccurate quantification of emission reductions.
2023
A review on the abundance, distribution and eco-biological risks of PAHs in the key environmental matrices of South Asia. Reviews of Environmental Contamination and Toxicology, 240
2017
2015