A spatial and fleet disaggregated approach to calculating the NOX emissions inventory for non-road mobile machinery in London

Desouza, Carl; Marsh, Daniel; Beevers, Sean; Molden, Nick; Green, D.C.

doi:10.1016/j.aeaoa.2021.100125

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…With detailed data, new policies can be implemented at the local level to increase the immediate impact on the local community [17]. Moreover, existing policies can be tested and improved [18], as direct agricultural subsidies can encourage agricultural-related carbon emissions [19], but subsidies directly aimed at reducing emissions can be beneficial to reducing emissions in the agricultural sector [20]. New procedures, such as new standards or better measuring devices, reduce overall emission inventory uncertainty and improve its accuracy [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Development of a Spatial Tier 2 Emission Inventory for Agricultural Tractors by Combining Two Large-Scale Datasets

Lončarević,

Ilinčić,

Šagi

et al. 2023

Sustainability

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Agricultural tractor emissions have a notable influence on total emissions and climate change. This is especially important when developing an agricultural machinery emission inventory since tractors are the most widely used agricultural machinery. However, as with other agricultural machinery, there is a significant lack of data concerning tractors. This study combined two large-scale datasets to develop a Tier 2 tractor emission inventory for the Republic of Croatia. The first dataset, which was collected via a large-scale survey with 8895 respondents, includes data on fuel consumption by machine and engine type. The second dataset, which is official data of the Ministry of the Interior, includes data on machinery age. Since there is no direct link between datasets, data on fuel consumption were calculated for each of 21 Croatian counties and were then linked to the corresponding municipalities’ tractor age and power rating of the vehicle fleet. The result was used to calculate tractor emissions by with a Tier 2 approach using the method listed in the 2019 EMEP/EEA emissions guidebook. The calculations were made for five exhaust emission components: carbon dioxide (CO2), carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOX) and particulate matter (PM). The continental counties had the highest emissions for all emission types, especially the Osječko-baranjska and Vukovarsko-srijemska counties. The Tier 2 emission inventory was compared to data calculated using the Tier 1 method on a county level. There were notable differences between the inventories for HC and PM emissions, which is mainly due to Tier 2 approach having different emission factors depending on vehicle age. The end result was compared to the already existing Tier 1 emission inventory on a county level.

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Section: Introductionmentioning

confidence: 99%

“…One example of such result format is the Environmental Protection Agency in the USA, which offers NRMM emission data disaggregated by federal states [27]. In the United Kingdom, data on NRMM emissions is available spatially in a visually engaging way [18].…”

Section: Introductionmentioning

confidence: 99%

Development of a Spatial Tier 2 Emission Inventory for Agricultural Tractors by Combining Two Large-Scale Datasets

Lončarević,

Ilinčić,

Šagi

et al. 2023

Sustainability

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“…Emissions of vehicle pollutants can harm human health and the environment [ 4 ]. According to statistics, in 2016, 2850 tons of nitrogen oxide emissions from non-road mobile machinery in the construction sector in London accounted for 7% of the total nitrogen oxide emissions in society [ 5 ]. Since the emission standards of construction machinery lag behind the emission standards of on-road vehicles [ 6 ], the emission limit requirements of construction machinery are relatively low.…”

Section: Introductionmentioning

confidence: 99%

Study on Emission Characteristics and Emission Reduction Effect for Construction Machinery under Actual Operating Conditions Using a Portable Emission Measurement System (Pems)

Chen

Li²,

Meng

et al. 2022

IJERPH

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With the acceleration of urban construction, the pollutant emission of non-road mobile machinery such as construction machinery is becoming more and more prominent. In this paper, a portable emissions measurement system (PEMS) tested the emissions of eight different types of construction machinery under actual operating conditions and was used for idling, walking, and working under the different emission reduction techniques. The results showed that the pollutant emission of construction machinery is affected by the pollutant contribution of working conditions. According to different emission reduction techniques, the diesel oxidation catalyst (DOC) can reduce carbon monoxide (CO) by 41.6–94.8% and hydrocarbon (HC) by 92.7–95.1%, catalytic diesel particulate filter (CDPF) can reduce particulate matter (PM) by 87.1–99.5%, and selective catalytic reduction (SCR) using urea as a reducing agent can reduce nitrogen oxides (NOx) by 60.3% to 80.5%. Copper-based SCR is better than vanadium-based SCR in NOx reduction. In addition, the study found that when the enhanced 3DOC + CDPF emission reduction technique is used on forklifts, DOC has a “low-temperature saturation effect”, which will reduce the emission reduction effect of CO and THC. The use of Burner + DOC + CDPF emission reduction techniques and fuel injection heating process will increase CO’s emission factors by 3.2–3.5 and 4.4–6.7 times compared with the actual operating conditions.

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“…For London: Road, railway, and aviation emissions were calculated based on the London Atmospheric Emissions Inventory (TfL 2020); water navigation data come from shipping emissions estimates byPLA and TfL (2017); and off-road mobile machinery data are included in the United Kingdom National Atmospheric Emissions Inventory(Desouza et al 2021). For California: Transport emissions estimates follow the 2006 IPCC Guidelines.…”

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confidence: 99%

Toward Credible Transport Carbon Dioxide Emissions Accounting in China

Xue¹,

Liu²

2022

WRIPUB

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A spatial and fleet disaggregated approach to calculating the NOX emissions inventory for non-road mobile machinery in London

Cited by 5 publications

References 4 publications

Development of a Spatial Tier 2 Emission Inventory for Agricultural Tractors by Combining Two Large-Scale Datasets

Development of a Spatial Tier 2 Emission Inventory for Agricultural Tractors by Combining Two Large-Scale Datasets

Study on Emission Characteristics and Emission Reduction Effect for Construction Machinery under Actual Operating Conditions Using a Portable Emission Measurement System (Pems)

Toward Credible Transport Carbon Dioxide Emissions Accounting in China

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