Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra
Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra
Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra
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<strong>PM2.5</strong> <strong>in</strong> the UK<br />
100<br />
60. At a local level, direct emissions of <strong>PM2.5</strong> from non-exhaust traffic sources will<br />
dom<strong>in</strong>ate exhaust emissions overall, assum<strong>in</strong>g control measures such as diesel<br />
<strong>particulate</strong> filters are effective. There needs to be a consolidated effort to reduce<br />
the uncerta<strong>in</strong>ty <strong>in</strong> methods for quantify<strong>in</strong>g emissions from tyre and brake wear<br />
and other non-exhaust processes for use <strong>in</strong> national and local <strong>in</strong>ventories.<br />
61. Inventories have not traditionally provided much, if any, detail on the<br />
component parts of <strong>PM2.5</strong>. This situation is improv<strong>in</strong>g with the availability of<br />
some <strong>in</strong>formation on the fractions of organic and elemental carbon <strong>in</strong> emissions<br />
from combustion sources, but there is much more that needs to be done to<br />
improve understand<strong>in</strong>g of the chemical composition of <strong>particulate</strong> <strong>matter</strong><br />
emissions from different sources.<br />
62. Section 4.2 listed several sources which are not <strong>in</strong>cluded <strong>in</strong> the NAEI. For<br />
modell<strong>in</strong>g <strong>PM2.5</strong>, it is necessary to look beyond this and consider areas where<br />
primary <strong>PM2.5</strong> emissions and emissions of its precursors are most uncerta<strong>in</strong> and<br />
further work is needed to improve methods for quantify<strong>in</strong>g them <strong>in</strong> a manner<br />
suitable for air <strong>quality</strong> models. In the follow<strong>in</strong>g list we highlight key sources (<strong>in</strong><br />
order of importance), selected because of their contribution to total primary<br />
<strong>PM2.5</strong> emissions <strong>in</strong> the <strong>in</strong>ventory and/or their levels of uncerta<strong>in</strong>ty and because<br />
of their potential <strong>in</strong>fluence on <strong>PM2.5</strong> concentrations locally or at certa<strong>in</strong> times;<br />
we also identify specific areas of uncerta<strong>in</strong>ty for further work:<br />
• non-exhaust vehicle emissions <strong>in</strong>clud<strong>in</strong>g tyre and brake wear, road abrasion<br />
and road dust resuspension;<br />
• fugitive dust emissions from construction, demolition, quarry<strong>in</strong>g, m<strong>in</strong>eral<br />
handl<strong>in</strong>g and <strong>in</strong>dustrial and agricultural processes and methods for<br />
quantify<strong>in</strong>g them nationally and locally;<br />
• <strong>PM2.5</strong> emissions from domestic and commercial cook<strong>in</strong>g;<br />
• small-scale waste burn<strong>in</strong>g and bonfires;<br />
• wood burn<strong>in</strong>g and the effectiveness of control measures;<br />
• biogenic emissions of NMVOCs, for which a def<strong>in</strong>itive <strong>in</strong>ventory or<br />
estimation method is required;<br />
• emissions of NH3 from agriculture, their temporal variability and methods<br />
for control;<br />
• emissions of SO2 and NOx from shipp<strong>in</strong>g, <strong>in</strong> particular their spatial<br />
distribution around ports and harbours, their temporal variability and future<br />
emissions;<br />
• exhaust emissions from off-road mach<strong>in</strong>ery used <strong>in</strong> construction and<br />
<strong>in</strong>dustry; and<br />
• exhaust emissions from diesel vehicles under real world driv<strong>in</strong>g conditions<br />
and the factors and technologies affect<strong>in</strong>g them.