Urban population exposure to NO<sub><i>x</i></sub> emissions from local shipping in three Baltic Sea harbour cities – a generic approach

Abstract

Abstract. Ship emissions in ports can have a significant impact on local air quality (AQ), population exposure and therefore human health in harbour cities. We determined the impact of shipping emissions in harbours on local AQ and population exposure in the Baltic Sea harbour cities Rostock (Germany), Riga (Latvia) and the urban agglomeration of Gdańsk–Gdynia (Poland) for 2012. An urban AQ study was performed using a global-to-local chemistry transport model chain with the EPISODE-CityChem model for the urban scale. We simulated NO2, O3 and PM concentrations in 2012 with the aim of determining the impact of local shipping activities on population exposure in Baltic Sea harbour cities. Based on simulated concentrations, dynamic population exposure to outdoor NO2 concentrations for all urban domains was calculated. We developed and used a novel generic approach to model dynamic population activity in different microenvironments based on publicly available data. The results of the new approach are hourly microenvironment-specific population grids with a spatial resolution of 100 m × 100 m. We multiplied these grids with surface pollutant concentration fields of the same resolution to calculate total population exposure. We found that the local shipping impact on NO2 concentrations is significant, contributing 22 %, 11 % and 16 % to the total annually averaged grid mean concentration for Rostock, Riga and Gdańsk–Gdynia, respectively. For PM2.5, the contribution of shipping is substantially lower, at 1 %–3 %. When it comes to microenvironment-specific exposure to annual NO2, the highest exposure to NO2 from all emission sources was found in the home environment (54 %–59 %). Emissions from shipping have a high impact on NO2 exposure in the port area (50 %–80 %), while the influence in home, work and other environments is lower on average (3 %–14 %) but still has high impacts close to the port areas and downwind of them. Besides this, the newly developed generic approach allows for dynamic population-weighted outdoor exposure calculations in European cities without the necessity of individually measured data or large-scale surveys on population data.

Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

“…To evaluate the urban population exposure to NO 2 and PM 2.5 , a combined air pollution, dynamic population activity and exposure modelling approach was developed and applied ( Figure 1). This approach is mainly based on the city-scale CTM EPISODE-CityChem [48] and a generic time-microenvironment-activity model to account for dynamic movements of the urban population within time and space in exposure estimations [46,49]. To investigate the impact of modal splits on exposure estimates, the generic TMA model was modified with new developments.…”

“…In Europe, about 8% of the urban population in the EU-28 was exposed to levels above the EU annual limit value of administrative records. Methods that are more recent apply GPS data [34,[39][40][41], agent-based modeling (ABM) approaches [42][43][44], or different time-microenvironment-activity (TMA) models [25,26,45,46] to estimate mobility patterns. Nevertheless, each of these methods has its own shortcomings.…”

“…The advantage of TMA models is that they enable a fast screening of dynamic populations in large areas, such as cities, regions, or countries. Moreover, TMA approaches for population exposure estimates can be applied in areas, where data on population activity are scarce [46], while most other approaches can only be transferred to other (urban) areas with considerable effort in data collection.…”

Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors

“…In dynamic approaches to exposure estimations, the population activity data is used to account for the diurnal variation in population numbers in different locations of the urban area. Therefore, we used a time-microenvironment-activity model [63] to assess the time-variant exposure of the population in a microenvironment (ME). A microenvironment is defined as the location or area with a relatively uniform pollutant concentration, such as the home or the workplace.…”

“…In the present study, the focus is on the indoor environments, because we are interested in the exposure in residential areas close to the harbor (ME home ). Thus, to account for the infiltration of outdoor air pollution into the indoor environments, we applied infiltration factors [63,64]. Infiltration factors (F inf ) for different pollutant species and different indoor environments are mostly derived from measurements and defined as:…”