Policy change driven by an AIS-assisted marine emission inventory in Hong Kong and the Pearl River Delta

Ng, Siu Kin; Loh, Christine; Chen, Lin; Booth, Veronica; Chan, Jimmy W.M.; Yip, Agnes C.K.; Li, Ying; Lau, Alexis K.H.

doi:10.1016/j.atmosenv.2012.07.070

Cited by 132 publications

(76 citation statements)

References 12 publications

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“…(1) 30 (U.S. EPA, 2000EPA, , 2008Ng et al, 2012): is the vessel arrived number, P is the average installed engine power (kW), LF is the average engine load factor, T is the average operation time in three activity modes (h), and EF is the emissions factor corresponding to the engine and fuel types (g/kW· h). 5…”

Section: ) Port-based Approachmentioning

confidence: 99%

“…The engine power and load factors of the ME were estimated using the Propeller Law based on the relationship between the instantaneous speed and the design speed, together with the detailed technical information of ship engine which was widely used in the estimation of ship emissions (ICF international, 2009). Owing to the lack of information and similar propulsion ratios for AE and AB 10 (Ng et al, 2012), the propulsion ratios and load factors for different ship types and operational modes were obtained from technical reports (U.S. EPA, 2008;Starcrest Consulting Group, 2009). Due to the difference in the DWT sub-class range and distribution of ship profile in different studies, adjustments were made for major ship types such that the AE and AB engine defaults better corresponded with the ship size and tonnage (Entec UK Limited, 2010;Ng et al 2012).…”

Section: ) Port-based Approachmentioning

confidence: 99%

“…Owing to the lack of information and similar propulsion ratios for AE and AB 10 (Ng et al, 2012), the propulsion ratios and load factors for different ship types and operational modes were obtained from technical reports (U.S. EPA, 2008;Starcrest Consulting Group, 2009). Due to the difference in the DWT sub-class range and distribution of ship profile in different studies, adjustments were made for major ship types such that the AE and AB engine defaults better corresponded with the ship size and tonnage (Entec UK Limited, 2010;Ng et al 2012). In addition, AE was assumed to be 15 off when the ship speed was more than 8 knots (except for container and passenger ships), and those ships with diesel-electric engines were assumed not to use their boilers.…”

Section: ) Port-based Approachmentioning

confidence: 99%

“…Previous studies indicated that the uncertainties in ship emissions were mainly introduced by time-inmode, load factors and emission factors (Yang et al, 2007;Ng et al, 2013), but these uncertainties were not quantified. In this study, AIS data were used to quantitatively characterize the uncertainties 25 associated with time-in-modes and load factors using a bootstrap simulation approach.…”

Section: Uncertaintymentioning

confidence: 99%

“…Emission factors were described per kWh Fan et al, 2016;Liu et al, 15 2016) and per kilogram fuel consumption (Jin et al, 2009;Bao et al, 2014) in different studies. To make emission factor units from the literature consistent and to analyze their uncertainties, a fuel consumption rate of 227 g/kWh was calculated for MHO and a rate of 217 g/kWh was calculated for marine diesel oil (MDO) and gas oil (Ng et al, 2012). In China, most RV engines were produced by Chinese manufacturers, such as Zichai, Weichai, and Guangchai.…”

Section: Emission Factorsmentioning

confidence: 99%

See 4 more Smart Citations

Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

Li¹,

Borken‐Kleefeld²,

Zheng³

et al. 2017

Preprint

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Abstract. Ship emissions contribute significantly to air pollution and pose health risks to residents of coastal areas in China, but the current accounting remains incomplete and coarse due to data availability and inaccuracy in estimation method. In this study, an Automatic Identification System 15 (AIS)-based integrated approach was developed to address this problem. This approach utilized Atmos. Chem. Phys. Discuss., https://doi

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Section: ) Port-based Approachmentioning

confidence: 99%

Section: ) Port-based Approachmentioning

confidence: 99%

Section: ) Port-based Approachmentioning

confidence: 99%

Section: Uncertaintymentioning

confidence: 99%

Section: Emission Factorsmentioning

confidence: 99%

See 3 more Smart Citations

Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

Li¹,

Borken‐Kleefeld²,

Zheng³

et al. 2017

Preprint

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Decomposition of the wind and nonwind effects on observed year‐to‐year air quality variation

Lau

Wong²,

Fung

2014

JGR Atmospheres

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Changes in emissions and wind are often identified as the two dominant factors contributing to year-to-year variations in the concentration of primary pollutants. However, because changes in wind and emissions are intertwined, it has been difficult to quantitatively differentiate their effects on air quality directly from observed data. In particular, if the annual mean concentration of pollutants is higher than the previous year, it is difficult to identify whether the deterioration in air quality is caused by wind blowing from more polluted regions or an increase in contributing emissions. In this paper, based on wind and pollution roses, we propose a method to differentiate the effects of wind and nonwind (e.g., emissions) changes using direct observation. An index (L) is first defined to quantify the validity of the linear decomposition. The method is then validated by idealized experiments, numerical experiments, and a 2 year observation data set from an actual emissions control program. Finally, we demonstrate the proposed method by studying long-term particulate matter (PM 10 ) variations in Hong Kong during 2000-2011. We find that for most of the period, the linear decomposition of the changes in annual PM 10 is valid (up to 90% confidence) and is dominated by the change in nonwind effects (e.g., emissions), whereas the average absolute effect from the wind variability is about 20%. Sensitivity analyses also suggest that our method should work in any location as long as the observed wind and pollution data have sufficient duration and resolution to resolve the corresponding wind and pollution roses.

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Importance of NOx control for peak ozone reduction in the Pearl River Delta region

et al. 2013

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[1] As major air pollutants and key precursors of several secondary air pollutants, nitrogen oxide (NOx) emissions are regulated in many countries. However, NOx control increases ozone concentrations when the ozone formation regime is volatile organic compound (VOC) limited. Although many studies have shown that NOx regulation reduces ozone levels over the long term, it is still of concern that NOx regulation increases short-term ozone levels in metropolitan regions, where ozone formation is found to be predominantly VOC-limited. The Pearl River Delta (PRD) in China is such a region. Our modeling sensitivity study shows that while NOx reduction in the PRD region may raise the mean ozone concentration, it can also decrease peak ozone levels. Similar changes are observed in the NOx and ozone data of the PRD regional air quality monitoring network (2006)(2007)(2008)(2009)(2010)(2011)(2012), lending further credence to our results. In the model, this NOx control effect is a result of the complicated spatial and diurnal variations of the ozone formation regime. In most of the PRD region, the formation regime is VOC-limited in the morning and becomes NOx-limited during peak ozone hours. Although some areas are always VOC-limited, their ozone concentrations are relatively low, and the ozone increases caused by NOx reduction generally do not cause higher ozone levels than the region's original ozone maxima. Several control scenarios are simulated to evaluate the effects of various possible control regulations. Our results show that in addition to VOC control, NOx control can be effective for reducing peak ozone concentrations in the PRD region.

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Policy change driven by an AIS-assisted marine emission inventory in Hong Kong and the Pearl River Delta

Cited by 132 publications

References 12 publications

Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

Decomposition of the wind and nonwind effects on observed year‐to‐year air quality variation

Importance of NOx control for peak ozone reduction in the Pearl River Delta region

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