Analysis of the effect of abiotic stressors on BVOC emissions from urban green infrastructure in northern Germany

Feldner, Josefine; Ramacher, Martin Otto Paul; Karl, Matthias; Quante, Markus; Luttkus, Marie

doi:10.1039/d2ea00038e

Cited by 4 publications

(2 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…EPISODE-CityChem was created to fill the gap between regional and micro-scale simulations for air quality and its output includes hourly or time-averaged concentrations of pollutants at specified locations within an urban area. The performance of EPISODE-CityChem and its compliance with quality criteria for regulatory purposes has been demonstrated in several urban-scale studies [40,[42][43][44][45][46][47].…”

Section: City-scale Air Quality Modellingmentioning

confidence: 99%

“…Hamburg was chosen as a case study because the high-resolution mapping of air pollution and SDG 11.6.2 is a demanding task (as discussed in Section 4.1), which necessitates a pre-establishment of the utilized methods for any urban area of study. The proposed modelling system for the intra-urban approaches is state-of-the-art and is already applied, tested, and demonstrated for the city of Hamburg [40,[42][43][44][45][46][47]. The overarching scope of this paper is to provide a demonstration of the EO potential in addressing and localizing the SDGs and, in particular, SDG Indicator 11.6.2.…”

Section: City-scale Air Quality Modellingmentioning

confidence: 99%

See 1 more Smart Citation

Localizing SDG 11.6.2 via Earth Observation, Modelling Applications, and Harmonised City Definitions: Policy Implications on Addressing Air Pollution

et al. 2023

Self Cite

View full text Add to dashboard Cite

While Earth observation (EO) increasingly provides a multitude of solutions to address environmental issues and sustainability from the city to global scale, their operational integration into the Sustainable Development Goals (SDG) framework is still falling behind. Within this framework, SDG Indicator 11.6.2 asks countries to report the “annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted)”. The official United Nations (UN) methodology entails aggregation into a single, national level value derived from regulatory air quality monitoring networks, which are non-existent or sparse in many countries. EO, including, but not limited to remote sensing, brings forth novel monitoring methods to estimate SDG Indicator 11.6.2 alongside more traditional ones, and allows for comparability and scalability in the face of varying city definitions and monitoring capacities which impact the validity and usefulness of such an indicator. Pursuing a more harmonised global approach, the H2020 SMURBS/ERA-PLANET project provides two EO-driven approaches to deliver the indicator on a more granular level across Europe. The first approach provides both city and national values for SDG Indicator 11.6.2 through exploiting the Copernicus Atmospheric Monitoring Service reanalysis data (0.1° resolution and incorporating in situ and remote sensing data) for PM2.5 values. The SDG Indicator 11.6.2 values are calculated using two objective city definitions—“functional urban area” and “urban centre”—that follow the UN sanctioned Degree of Urbanization concept, and then compared with official indicator values. In the second approach, a high-resolution city-scale chemical transport model ingests satellite-derived data and calculates SDG Indicator 11.6.2 at intra-urban scales. Both novel approaches to calculating SDG Indicator 11.6.2 using EO enable exploration of air pollution hotspots that drive the indicator as well as actual population exposure within cities, which can influence funding allocation and intervention implementation. The approaches are introduced, and their results frame a discussion around interesting policy implications, all with the aim to help move the dial beyond solely reporting on SDGs to designing the pathways to achieve the overarching targets.

show abstract