Trends in France for achieving the Agenda 2030 sustainable development goals (SDG)

SDG11 – Make cities and human settlements inclusive, safe, resilient and sustainable

Measuring stations exceeding the daily threshold for long-term human health protection for PM₁₀ during the year – urban areas with more than 250,000 inhabitants
Change*Latest value**Trend for achieving the SDG by 2030

-0.8 points from 2017 to 2022

YearValue
20171,71
20180,88
20190,87
20200,00
20210,00
20220,92
0.92%
Favourable

The percentage of urban areas exceeding the regulatory thresholds for health protection for PM10 (solid particles less than 10 µm in diameter) has been falling since 2011, after marked fluctuations between 2007 and 2010: 19% of urban areas exceeded the thresholds in 2011, and only 1.2% in 2022. This even reached 0% in 2020 and these historically low recorded contents were due to the measures introduced to combat the spread of Covid-19.


Measuring stations exceeding the daily threshold for long-term human health protection for PM₁₀ during the year – urban areas with 50,000 to 250,000 inhabitants
Change*Latest value**Trend for achieving the SDG by 2030

-0.7 points from 2017 to 2022

YearValue
20171,44
20180,69
20190,72
20200,00
20213,00
20220,77
0.77%
Favourable

Between 2007 and 2011, medium-sized and large urban areas were the most impacted by exceedences of regulatory thresholds. Since 2014, there has been no marked difference in the size of the urban areas concerned. The majority of measuring stations involved are in close proximity to road traffic or urban backgrounds. For PM10 (solid particles less than 10 µm in diameter), 153 urban areas have always respected the regulatory thresholds for the protection of health over the period 2007-2022.


Annual mean PM₁₀ concentrations at urban background stations
Change*Latest value**Trend for achieving the SDG by 2030

-7.3% from 2017 to 2022

YearValue
201717,80
201817,10
201916,30
202015,10
202115,40
202216,50
16.5 μg/m³
Favourable

The average annual concentrations of PM10 (solid particles less than 10 µm in diameter) have fallen, albeit moderately. A slight increase in concentrations was recorded for PM10 and PM2.5 between 2020 and 2022, but the 2022 levels remain stable versus 2019. In 2022, the average annual concentrations at urban background stations was 16.5 µg/m3 for PM10. Despite an overall declining trend for PM10 and PM2.5, annual variations have nonetheless been observed as the presence of particulate matter in the air is linked to several factors: emissions from human activities or natural sources (sandstorms for example); the formation of secondary particles from emissions of precursor gases such as NH3; meteorological conditions; and the long-range transport of pollutants.


Proportion of the population living in overcrowded housing
Change*Latest value**Trend for achieving the SDG by 2030

-0.3 points from 2013 to 2020

YearValue
20138,40
20208,10
8.1%
Moderately favourable

In 2016, over 5 million people, or 8.2% of the population excluding Mayotte, were living in overcrowded housing, i.e. in a household of two or more living in a dwelling with an insufficient number of rooms for the size of their household. This situation affects 3.2% of the population living in houses and 16.5% of those living in an apartment. The classification of public administration spending per function showed that €54.6 billion was mobilised for housing and public facilities in 2022 (2.1% of GDP), including €31.9 billion for housing (1.2% of GDP), €22.1 billion of which was for social services and €9.8 billion for building subsidies (including tax credits [1]) and operating expenses for administrations.


Artificialized land
Change*Latest value**Trend for achieving the SDG by 2030

+0.4 points from 2015 to 2020

YearValue
20158,70
20168,80
20178,90
20189,00
20199,00
20209,10
9.1%
Moderately unfavourable

Over the past decade, 24,000 ha of natural, agricultural and forest areas have been consumed annually on average in France. This issue concerns the whole of France, but predominantly in sparsely populated areas where 61% of land has been consumed. This has ecological (erosion of biodiversity, worsening of waterflow risk, limitation of carbon storage) and socio-economic (cost of public facilities, increased travel time and energy bill for households, degradation of abandoned land, reduction in the potential of agricultural production, etc.) consequences. The phenomenon is highly concentrated: 5% of communes account for 38% of land consumption. 61.6% of land consumption is in areas with low demand for property. Rural communes accounted for 65.4% of land consumption between 2013 and 2019, for 21.8% new inhabitants and 29.7% new households.


Recycled municipal waste
Change*Latest value**Trend for achieving the SDG by 2030

+4.1 points*** from 2016 to 2021

YearValue
201639,70
201740,20
201840,70
201941,00
202041,70
202143,80
43.8%
Moderately unfavourable

*** Insufficient progress with regard to the target to be reached.

Note: estimated 2016-2021 data

In 2020, France produced 309 million tonnes (Mt) of waste, 46 Mt less than in 2010. The construction sector generated 213 Mt tonnes of waste and other economic activities and local authorities generated 64 Mt, while households produced 34 Mt, representing 10.8% of the total. Local authorities are developing the sorting of household and commingled waste and the number of Extended Producer Responsibility sectors is growing, which allows for better processing of municipal waste. Between 2016 and 2021, the recycling rate for material and organic waste increased from 39.7% to 43.8%.


Source: INSEE, Dashboard of national indicators for monitoring the Sustainable Development Goals – published February 2024. Statistics processed by SDES (ministerial Statistical Data and Studies Department) - Only available in French. (Insee, Tableau de bord des indicateurs pour le suivi national des objectifs de développement durable - paru en février 2024. Traitements SDES)

*Change: since the latest available value, change over a period of 5 years (longer or shorter depending on data availability).

**Latest value: value corresponding to the last year of the trend graph.

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