Air pollution affects the environment negatively, boosts climate change, and is the cause of millions of deaths per year, first and foremost affecting the people living in urban areas. Since the early 20th century, many cities have been planned around cars, which are the main contributors to the bad air quality. However, after the Covid-19 pandemic, cities have been reshaped to enhance active travel and to provide more space for greenery. In London, this reassessment of the urban areas has led to the Low-Traffic Neighbourhoods (LTNs). The LTNs origins from 2019, however, most of them were implemented during the pandemic because of the crucial times demanding social distance, while also enabling people to walk and cycle more in their local borough. The LTNs only allow residents, emergency vehicles and blue badge carriers to enter, if travelling by a motorised vehicle. The scheme further aims for more greenery to be implemented. The aim of this thesis is to study the impact from the LTNs on the air quality of the local area, specifically regarding PM₁₀ and NO_X, by using openly available data from the Imperial College London. Furthermore, the existing Green Infrastructure (GI) around each sensor, as well as the traffic, has been studied and compared to the air pollutant levels. This has been done to be able to analyse the air pollutants in relation to the surrounding GI and the level of traffic. The methodology further consists of mapping the air pollutants measured by the sensors; a statistical analysis; an interview with Sally Oldfield, the Nature Conservation Manager at Islington Ecology Centre; and field studies to the sensors used in the thesis, both the ones in LTNs and the ones in non-LTNs. The boroughs included in the study are the City of London, Islington, Wandsworth, and Westminster. 

Previous research about the LTNs have focused on health and social issues, and the research about traffic schemes have focused on Low Emission Zones (LEZ) and Ultra Low Emission Zones (ULEZ). Studies on the air quality impact of the Covid-19 lockdowns have been done on New York, Madrid and Barcelona. The previous research on air pollutants in urban areas show a difficulty in mapping the movement of the pollutants hence the varied variables having an impact, such as wind, weather, the height and positions of the surrounding buildings. Research on the impact on the air quality from GI in general, has shown that the efficiency is dependent on the planning, type and size of the vegetation, as well as the distance to the emission source. However, the studies on GI are uncertain in how effective it is in terms of air quality improvement. 

The result of this thesis shows a decline in NO_X- and PM₁₀-values after the implementation of the LTN by all sensors. The annual patterns further show that the yearly trends of the pollutants remained, however the magnitude is lower after the implementation of the LTNs. The daily patterns show varied results, where NO_X has clear connections to the traffic, and the sources of PM10 are uncertain. Lastly, the statistical analysis showed that the data series came from different distributions, except the PM₁₀-values by one of the sensors in Islington. Although a reduction was seen by all sensors, this might be because of, e.g., the Covid-19 pandemic. Furthermore, a correlation between GI and lower values of the pollutants could be seen by some sensors, however the results varied, making it difficult to distinguish any correlation. In conclusion, the absence of traffic can be seen to reduce the air pollutants NO_X and PM₁₀, where GI might have a positive impact. Suggesting to reshape urban areas to enable active travel, and reduce the possibilities to travel by car, with the exception of blue badge carriers and emergency vehicles. Although the impact on air improvement from GI is uncertain, it is suggested to be incorporated in the planning due to its other benefits such as recreation, well- being, and biodiversity.