568 research outputs found
Identifying drivers for the intra-urban spatial variability of airborne particulate matter components and their interrelationships
Full text linkThe aim of this work was to compare the variability in an urban area of fine particles (PM2.5), ultrafine particles (UFP) and black carbon (BC) and to evaluate the relationship between each particle metric and potential factors (local traffic, street topography and synoptic meteorology) contributing to the variability. Concentrations of the three particle metrics were quantified using portable monitors through a combination of mobile and static measurements in the city of Edinburgh, UK. The spatial variability of UFP and BC was large, of similar magnitude and about 3 times higher than the spatial variability of PM0.5-2.5 (the PM size fraction actually quantified in this work). Highest inter-daily variability was observed for PM0.5-2.5, which was approximately 2 times higher than inter-daily variability of BC and UFP. Elevated concentrations of UFP and BC were observed along streets with high traffic volumes whereas PM0.5-2.5 showed less variation between streets and a footpath without road traffic. Both BC and UFP were significantly correlated with traffic counts, while no significant correlation between PM0.5-2.5 and traffic counts was observed. BC was significantly correlated with UFP, with significantly different regression slopes between working days and non-working days implying that the increased number of diesel powered heavy goods vehicles during working days contributed more to BC than to UFP. It is concluded that variations in BC and UFP concentrations were mainly determined by the nearby traffic count and varying background concentrations between days, while variation in PM0.5-2.5 concentration was mainly associated with regional sources. These findings imply the need for different policies for managing human exposure to these different particle components: control of much BC and UFP appears to be manageable at local scale by restricting traffic emissions; however, abatement of PM2.5 requires a more strategic approach, in cooperation with other regions and countries on emissions control to curb long-range transport of PM2.5 precursors
Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study
Full text linkAtmospheric chemistry transport models (ACTMs) are widely
used to underpin policy decisions associated with the impact of potential
changes in emissions on future pollutant concentrations and deposition. It
is therefore essential to have a quantitative understanding of the
uncertainty in model output arising from uncertainties in the input
pollutant emissions. ACTMs incorporate complex and non-linear descriptions
of chemical and physical processes which means that interactions and
non-linearities in input–output relationships may not be revealed through
the local one-at-a-time sensitivity analysis typically used. The aim of this
work is to demonstrate a global sensitivity and uncertainty analysis
approach for an ACTM, using as an example the FRAME model, which is
extensively employed in the UK to generate source–receptor matrices for the
UK Integrated Assessment Model and to estimate critical load exceedances. An
optimised Latin hypercube sampling design was used to construct model runs
within ±40 % variation range for the UK emissions of SO2, NOx, and NH3, from which regression coefficients for each
input–output combination and each model grid ( > 10 000 across the
UK) were calculated. Surface concentrations of SO2, NOx, and NH3 (and of deposition of S and N) were found to be predominantly
sensitive to the emissions of the respective pollutant, while sensitivities
of secondary species such as HNO3 and particulate SO42−, NO3−, and NH4+ to pollutant emissions were more complex
and geographically variable. The uncertainties in model output variables
were propagated from the uncertainty ranges reported by the UK National
Atmospheric Emissions Inventory for the emissions of SO2, NOx, and NH3 (±4, ±10, and ±20 %
respectively). The uncertainties in the surface concentrations of NH3
and NOx and the depositions of NHx and NOy were dominated by
the uncertainties in emissions of NH3, and NOx respectively,
whilst concentrations of SO2 and deposition of SOy were affected
by the uncertainties in both SO2 and NH3 emissions. Likewise, the
relative uncertainties in the modelled surface concentrations of each of the
secondary pollutant variables (NH4+, NO3−, SO42−, and HNO3) were due to uncertainties in at least two
input variables. In all cases the spatial distribution of relative
uncertainty was found to be geographically heterogeneous. The global methods
used here can be applied to conduct sensitivity and uncertainty analyses of
other ACTMs
Surface atmosphere dynamics of reactive trace gases and water-soluble aerosol components above agricultural grassland and tropical rainforest
Full text linkThe interaction between biosphere and atmosphere in the cycling of gas and
aerosol species is of key importance in considering overall emission and deposition
rates of nutrients and pollutants. Understanding of the biosphere-atmosphere
processes that govern these cycles is critical to modelling overall global concentrations
of atmospheric aerosols and trace gases, which in turn is vital to developing
predictions for overall global climate and international pollution burdens.
However, to understand these processes, more measurements over a variety of
different ecosystems are required, preferably measurements which are taken in
real time, which are of high temporal resolution, and record a variety of species
simultaneously and at potentially low background concentrations.
This thesis presents work in which the Gradient of Aerosols and Gases Online
Registration (GRAEGOR), an instrument which employs a modified form of
the aerodynamic gradient method (AGM) to determine fluxes from measured
concentrations, was used to determine concentrations and fluxes of the trace gases
NH3, HCl, HONO, HNO3 and SO2 and the water-soluble aerosol species NH+4, Cl-, NO--2 , NO-3 and SO2-4 above agricultural grassland and tropical rainforest.
Measurements of the suite of trace gases and aerosols were conducted from May
2016 to June 2016 at the Easter Bush agricultural grassland site (Midlothian,
United Kingdom). From these measurements, full time scale and diel profiles for
concentrations, fluxes and deposition velocities for each species were developed.
Through the use the conservative exchange fluxes of tot-NH-4 and tot-NO-3 , it
was found that a ground source of HNO3 existed after a fertilisation event, which
after scavenging by volatilised NH3 formed ammonium nitrate aerosol. Diel
cycle variation in HONO concentrations showed a background concentration of
HONO during midday, contrary to expectations regarding the chemical behaviour
of HONO. This suggests a potential daytime source of HONO at the site. A link
between the deposition velocities for Cl-, NO-3 and SO2-4 and a proxy for aerosol
size provided evidence for the modelled link between increasing deposition velocity
with increasing aerosol size. A comparison between the HONO concentrations
measured by the GRAEGOR and the HONO concentrations measured by the
Long Path Absorption Photometer (LOPAP) was also conducted, which found
that the GRAEGOR records a higher concentration of HONO in comparison to
the LOPAP, suggesting the presence of artefact factors within the GRAEGOR
when measuring HONO. A modified form of a correction factor was developed to
account for this HONO artefact. A similar comparison for NH3 recorded by the
GRAEGOR and NH3 recorded by the Quantum Cascade Laser (QCL) was also
conducted, finding that the QCL overestimated NH3 concentrations.
Measurements of trace gases and aerosols above tropical rainforest were carried
out from October 2017 to November 2017 at the Amazon Tall Tower Observatory
(ATTO) site (Amazonas, Brazil). This was during the tropical dry season.
Measurements of HONO concentration found that values remained above the
detection limit of the instrument, even during daytime. Calculations of HONO
flux found small but significant emissions of the trace gas in the early morning,
suggesting formation of HONO below canopy during the evening followed by
venting of the gas to above the canopy during the morning. It was found that
local, regional and global sources of biomass burning led to periods of elevated
SO2 concentrations, with an associated increase in the dry deposition of SO2
and associated SO2-4 containing aerosol. Emissions of all measured aerosols,
particularly Cl_, were observed throughout the campaign, which may be related
to emissions of primary biological aerosol particles (PBAPs).
Bi-directional exchange of NH3 was measured during the campaign at ATTO. In
combination with ancillary measurements of leaf wetness data, a novel parameterisation
of NH3 emission and deposition to tropical rainforest was developed.
This parameterisation was able to accurately simulate the bi-directional pattern
of observed NH3 fluxes at the rainforest site. Based on the observed pattern of
NH3 emissions occurring during periods where measured leaf wetness was low, it
was concluded that emissions were driven by stomatal exchange of leaf NH3 with
the atmosphere.
This study has demonstrated that observed HONO concentrations above agricultural
grassland are sometimes not consistent with predicted chemical pathways
based on HONO photodissociation, and that there exists a potential source
of HONO that affects overall daytime concentrations. Similarly, emissions of
HONO have been demonstrated to exist from tropical rainforest, with a proposed
pathway from soil emissions to the atmosphere. Furthermore, this study
has conducted simultaneous measurements of the individual components of the
NH3-HNO3-NH4NO3 triad, noting apparent formation of NH4NO3 from urea application
to agricultural grassland. Finally, bi-directional exchange of NH3 from
the rainforest has been demonstrated to occur during the tropical dry season, particularly
during the warm, dry periods at the canopy level that are characteristic
of the hours immediately following noon
Modelling of global atmospheric reactive nitrogen and sulfur and their mitigation strategies
Full text linkThe reduction of atmospheric reactive N (Nr) and S (Sr) species is a key objective for air quality control policies because they contribute to the formation of PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm), which have significant effects on human health and climate, and their deposition affect ecosystem biodiversity. As a range of emission sources and atmospheric chemical and physical processes contribute to Nr and Sr concentrations, atmospheric chemistry transport models (ACTMs) are an essential tool to identify important processes controlling their impacts and effective mitigation. Here, the EMEP MSC-W ACTM coupled with WRF meteorology at 1º×1º resolution is used. The chemical climate for Nr and Sr pollution has changed dramatically in the past two decades, it is therefore necessary to update our understanding of global Nr and Sr chemistry and investigate their mitigation under current atmospheric state. Thus, the aims of the thesis are (i) to evaluate the global model simulation of reduced N (RDN), oxidised N (OXN), and oxidised S (OXS) against ambient measurements; (ii) to analyse current global and regional budgets, fluxes, and lifetimes of RDN, OXN, and OXS, quantifying important processes controlling their regional distributions in the atmosphere; and (iii) to quantify the sensitivities of emissions reductions for the mitigation of PM2.5, Nr and Sr species.
Firstly, the evaluation of the EMEP MSC-W model is conducted both spatially and temporally, covering 10 monitoring networks worldwide measuring surface concentrations and wet deposition. Model simulations for 2010 compared use of both HTAP and ECLIPSEE (ECLIPSE annual total with EDGAR monthly profile) emissions inventories; those for 2015 used ECLIPSEE only. Simulations of primary pollutants are somewhat sensitive to the choice of inventory in places where regional differences in emissions between the two inventories are apparent (e.g., China), but much less so for secondary components. Comparisons of 2010 and 2015 annual concentrations between model and measurement demonstrate that the model captures well the overall spatial and seasonal variations of the major inorganic pollutants NH₃, NO₂, SO₂, HNO₃, NH₄⁺, NO₃⁻, SO₄²⁻ , and their wet deposition in East Asia, Southeast Asia, Europe, and North America. The model shows better correlations with annual average measurements for networks in Southeast Asia (Mean R for 7 species: /R₇ = 0.73), Europe ( /R₇ = 0.67) and North America ( /R₇ = 0.63) than in East Asia ( /R₅ = 0.35) (data for 2015), which suggests potential issues with the measurements in the latter network. The evaluation of wet deposition shows that the greatest consistency is in North America (R: 0.75-0.82), followed by
Southeast Asia (R: 0.51-0.68), Europe (R: 0.61-0.64), and East Asia (R: 0.13-0.59). Model-measurement bias varies between species in different networks. The greater uniformity in spatial correlations than in biases as revealed in this work suggests that the major driver of model-measurement discrepancies (aside from their differing spatial representativeness and uncertainties in measurements) are shortcomings in absolute emissions rather than in modelling the atmospheric processes.
Secondly, the EMEP-WRF model is used to undertake a present-day (2015) global and regional quantification of Nr and Sr concentrations, fluxes, and lifetimes, which are quantities that cannot be derived from measurements alone. In areas with high levels of RDN (NH3 + NH4+), OXN (NOx + HNO3 + HONO + N2O5 + NO3- + Other OXN species), and OXS (SO2 + SO42-), RDN is predominantly in the form of NH3 (NH4+ typically <20%), OXN has majority gaseous species composition, and OXS predominantly comprises SO42- except in areas near major SO2 sources.
Most continental regions are now ‘ammonia rich’, and more so than previously, which indicates that whilst reducing NH3 emissions will decrease RDN concentration it will have little effect on mitigating secondary inorganic aerosol (SIA). South Asia is the most ammonia-rich region. Coastal areas around East Asia, northern Europe, and north-eastern United States are ‘nitrate rich’ where NH4NO3 formation is limited by NH3. These locations experience transport of OXN from the adjacent continent and/or direct shipping emissions of NOx but NH3 concentrations are lower. The least populated continental areas and most marine areas are ‘sulfate rich.’ Deposition of OXN (57.9 TgN yr-1, 51%) and RDN (55.5 TgN yr-1, 49%) contribute almost equally to total nitrogen deposition. OXS deposition is 50.5 TgS yr-1. Dry deposition of NH3 is the largest contributor to RDN deposition in most continental regions except for remote areas where NH3 emissions are small and RDN deposition is mainly determined by transport of NH4+. The two largest contributors to OXN deposition in all regions are HNO3 and coarse NO3- (via both wet and dry deposition). The tropospheric lifetime of NH3 (1.6 days) is much shorter than that of NH4+ (8.9 days), consistent with a global NH4+ burden (68% of total RDN burden) almost double that of NH3 (32%). Fine NO3- only constitutes 10% of global nitrate burden, albeit fine NO3- dominates in eastern China, Europe, and eastern North America. It is therefore important to account for contributions of coarse nitrate to tropospheric nitrate budgets. Lifetimes of RDN, OXN, and OXS species vary by a factor of 4 across continental regions with East and Southeast Asia generally having the shortest lifetimes. South Asia is the largest net exporter of RDN (2.21 TgN yr-1, 29% of its annual emission) and OXS (1.62 TgS yr-1, 37%). Africa is the largest net exporter of OXN (1.92 TgN yr-1, 22%). Despite having the largest RDN emissions and deposition, East Asia has only small net export and is therefore largely responsible for its own RDN pollution.
Finally, the sensitivity of Nr, Sr, and PM2.5 to 20% and 40% individual and collective reductions in anthropogenic emissions of NH3, NOx, and SOx relative to the 2015 baseline is investigated. Regional comparisons reveal that the individual emissions reduction has multiple co-benefits and small disbenefits on different species, and those effects are highly geographically variable. A 40% NH3 emission reduction decreases regional average NH3 concentrations by 47-49%, but only decreases NH4+ by 18% in Euro_Medi, 15% in East Asia, 12% in North America, and 4% in South Asia. This order follows the regional ammonia-richness. A disbenefit is the increased SO2 concentrations in these regions (10-16% for 40% reductions) because reduced NH3 levels decrease SO2 deposition through altering atmospheric acidity. A 40% NOx emission reduction reduces NOx concentrations in East Asia by 45%, Euro_Medi and North America by ~38%, and South Asia by 22%, whilst the regional order is reversed for fine NO3-, which is related to enhanced O3 levels in East Asia (and also, but by less, in Euro_Medi), and decreased O3 levels in South Asia (and also, but by less, in North America). Consequently, the oxidation of NOx to NO3- and of SO2 to SO42- is enhanced in East Asia but decreased in South Asia, which causes a less effective decrease in NO3- and even an increase in SO42- in East Asia, but quite the opposite in South Asia. For regional policy making, it is thus vital to reduce three precursors together to minimise such adverse effects. A 40% SOx emission reduction is slightly more effective in reducing SO2 (42-45%) than SO42- (34-38%), whilst the disbenefit is that it yields ~12% increase in NH3 total deposition in the four regions which further threatens ecosystem diversity. This work also highlights important messages for policy-makers concerning the mitigation of PM2.5. More emissions controls focusing on NH3 and NOx are necessary for regions with better air quality such as northern Europe and eastern North America. In East Asia, the three individual reductions are equally effective, whilst in South Asia only SOx reduction is currently effective. The geographically-varying non-one-to-one proportionality of chemical responses of Nr, Sr, and PM2.5 to emissions reductions revealed by this work show the importance of both prioritising emissions strategies in different regions and combining several precursor reductions together to maximise the policy effectiveness.
In summary, the comprehensive model evaluation, as the opening study of this thesis, supports the application of this model framework for analysis of current Nr and Sr budgets (second study) which then provides theoretical explanations for responses of Nr and Sr to potential emission controls (third study). By demonstrating the model’s capability of simulating global atmospheric chemistry and transport and presenting an update of current atmospheric state in terms of particle formation, this thesis provides useful suggestions for global and regional policymakers to mitigate PM2.5 pollution and reduce N and S deposition
Improvement of modelling human exposure to NO₂ in cities in China: the case of Guangzhou
Full text linkNitrogen dioxide (NO₂) is an air pollutant identified as a public health concern. Exposure to NO₃ is associated with a number of adverse respiratory health effects, and ultimately with premature mortality. It also contributes as a precursor to formation of tropospheric ozone (O₃) and ammonium nitrate fine particulate matter (PM₂.₅, particles with aerodynamic diameters <2.5 µm).
Rapid economic growth, industrialization, and urbanization in China are leading to substantial adverse air quality issues, including high levels of annual mean NO₂ concentrations. It is important to quantify human exposure to NO₂ to evaluate its health impacts and to assess the effectiveness of mitigation approaches. Since 2013, the China National Environmental Monitoring Centre (CNEMC) has been implementing a nationwide monitoring network for the routine measurement of ambient air pollutant concentrations. Previous studies into population exposure used the monitor data as a proxy for human exposure. However, NO₂ concentrations within cities have shown high spatial variations. The monitoring network only provides concentrations at a limited number of discrete points, which is inadequate to describe the spatial variability of urban air pollution. New methods need to be developed to tackle these challenges. The overall aim of this PhD project is to explore modelling approaches for better estimating intra-urban variability of NO₂ for human exposure research in China, given the obstacles in data availability of monitored data, emission inventories, and other highly spatially resolved data in China.
Guangzhou is chosen as an exemplar geographic domain. It is the third largest city in China, with a population of 14 million and an area of 7,433 km², and does not currently meet the Chinese air quality standard (GB 3095-2012) for NO2, which is set as 40 µg m-3 as an annual average. The Guangzhou local government has an air quality compliance plan that aspires to annual average NO₂ concentrations of 40 μg m⁻³ by 2020.
Two modelling methods are widely used to simulate pollutant concentrations at relatively high spatial resolution within urban areas: dispersion modelling and land-use regression (LUR) modelling. Dispersion modelling aims to simulate the physical chemical processes that link the emissions of pollutants from sources and their transport and dispersion. Recently, urban dispersion models have been developed in Beijing, Shanghai, Chongqing, Hangzhou, Kunming, Hong Kong, Harbin, Lanzhou, Urumqi, Liaoning province, Jinan, Fushun, and Macao using ADMS and AERMOD. Substandard modelling results can arise due to insufficient monitor data and incomplete or inaccurate emission inventories. LUR relies on existing measurements to derive the statistical relationship between pollutant concentrations at a given location and predictor variables representing the emission and dispersion of air pollutants. An appropriately sized and designed monitoring network is an important component for the development of a robust LUR model.
LUR models are now being applied to simulate pollutant concentrations with high spatial resolution in Chinese urban areas. Current challenges and future needs in employing LUR approaches were identified first in this PhD work. Details of twenty-four recent LUR models for NO₂ and PM₂.₅/PM₁₀ (particles with aerodynamic diameters <10 µm) were reviewed. LUR modelling in China is currently constrained by a scarcity of input data, especially air pollution monitor data. There is an urgent need for accessible archives of qualityassured measurement data and for higher spatial resolution proxy data for urban emissions, particularly in respect of traffic-related variables. The rapidly evolving nature of the Chinese urban landscape makes maintaining up-to-date land-use and urban morphology datasets essential for LUR models. Given the limited number of monitoring sites in Guangzhou and the geographical scale of the domain, an integrated modelling approach combining dispersion modelling with ADMS-Urban and LUR has been developed in this PhD work. ADMS-Urban was applied in Guangzhou using input data including emissions from the Multi-resolution Emission Inventory for China (MEIC), road geometry from OpenStreetMap, and hourly meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Concentrations of NO₂ were simulated by ADMS-Urban at 83 ‘virtual’ monitoring sites spanning the six districts in Guangzhou and weighted according to population (since the overall focus is estimation of population NO₂ exposure). The LUR model was validated against both the 83 virtual sites (adj R²: 0.96, RMSE: 5.48 μg m⁻³; LOOCV R²: 0.96, RMSE: 5.64 μg m⁻³) and, independently, against available observations (n = 11, R²: 0.63, RMSE: 18.0 μg m⁻³). The modelled population-weighted long-term average concentration of NO₂ across Guangzhou in 2017 was 52.5 μg m⁻³, which contributes an estimated 7,270 (6,960−7,620) attributable deaths.
This hybrid modelling approach is then applied to explore the scale of emissions reductions necessary within the Guangzhou domain to achieve compliance with a number of different interpretations of an NO2 concentration target of 40 μg m⁻³. (The Guangzhou Ambient Air Quality Compliance Plan does not explicitly state how to practically assess compliance.) The modelling results show that achieving compliance requires different levels of emission reductions, depending on how the concentration target was defined; for example, to reduce the average concentration at all monitoring sites below 40 µg m⁻³, requires a 60% reduction of emissions from all source sectors. In contrast, to attain ≤40 µg m⁻³ concentration across the whole of Guangzhou requires a 90% emissions reduction. The impacts of the emissions reductions on NO₂-attributable premature mortality are also calculated and illustrate that use of a concentration value as a target does not fully convey the underlying health gains even when the target is not met.
In the final part of this thesis, the findings and implications from the modelling studies are discussed in the context of current air quality management system in China. Whilst the results are based on detailed and consistent model results for the specific situation in Guangzhou, they are relevant for, and can provide evidence to, decision makers designing effective air pollution control policies in other fast-growing megacities in China and elsewhere globally. The challenges and limitations for the development of a highly spatial revolved model for human exposure are discussed
Developing a land use regression model for NO2 concentrations in Guangzhou, China
No full textHealth impacts of air pollution are widely recognised where exposure to NO2 increases the risk of respiratory diseases and mortality. High levels of ambient NO2 are common in megacities because of the rapid economic and industrial growth. Due to a large heterogeneity in observed pollutant concentrations, modelling concentrations is traditionally complex. Land use regression (LUR) techniques with the use of GIS have been developed where measurements of NO2 are utilised together with predictor variables to predict NO2 concentrations at unsampled locations. In this work a LUR model has been developed for Guangzhou, southern China. The resulting model was able to explain 96% of the variance in NO2 concentrations effectively demonstrating strong predictive power. The predictor variables included in the final model were green space in a 5000 m buffer, emissions from major roads in a 300 m buffer, green space in a 100 m buffer and the length of all roads in a 50 m buffer. Model validation presented low error in value prediction and confirmed model prediction ability. The LUR model was utilised to quantify the number of attributable deaths from exposure to NO2. A total of 7515 people was estimated to experience premature deaths of the total annual deaths in Guangzhou. The LUR model developed represents a highly relevant and valuable tool for assessing air quality issues in Guangzhou
Representativeness and application of long-term trace gas and photolysis measurements for evaluating local air quality
Full text linkNetworks of long-term measurements of trace gases are critical for understanding spatio-temporal trends in air pollutants. This data is used to assess long-range and trans-boundary transport of emissions, quantify effects on public health, develop mitigation
strategies and examine the impact of implemented policy changes. As part of the European Monitoring and Evaluation Programme (EMEP), the UK operates two “super sites” which have provided a suite of co-located measurements for this purpose. These
supersites have been running for decades, and are located in rural background conditions, with the intention of being representative of the north and south of the country.
A Monitor for AeRosols and Gases in ambient Air (MARGA; Metrohm Applikon, NL)
has been included in these sites’ measurements for over a decade. However its gaseous
measurements of nitric acid (HNO3) have been demonstrated to include potential artefacts from other oxidised reactive nitrogen species (NOy), such as dinitrogen pentoxide
(N2O5). This interference has not yet been formally quantified. Other NOy measurements at either site are infrequent. Nitryl chloride (ClNO2) in particular was first measured in the UK in 2012, and has been measured only sporadically since.
Meteorological variables are similarly measured in networks to provide locally representative data, which are utilised in atmospheric chemistry and chemical transport
models. Photolysis reactions are key drivers of atmospheric chemistry, initiating many
reaction routes via the production of reactive radical species. As such, accurate estimation of photolysis rate constants (or photolysis frequencies; j-values) are imperative
for understanding subsequent reactions and predicting accurate pollutant concentrations. Photolysis rate constants are highly influenced by local meteorology (e.g. clouds, aerosols), but capturing the spatio-temporal variability of these changing conditions is
challenging, and often computationally costly. Consequently, modelled j-values are often parameterised or determined for unrepresentative local conditions, and results are
not validated beyond model conception. Some studies apply adjustment factors to these
model results to account for local conditions, but these have not yet been standardised
nor explored.
Part of this PhD research presents a systematic analysis of a measurement-driven adjustment factor (MDAF) to adjust clear-sky or cloud-free modelled j-values to capture
changes in the local meteorology. MDAFs were derived from the ratios of j-values
from both filter- and spectral radiometer measurements and clear-sky estimates from
the Tropospheric Ultraviolet and Visible radiative transfer model (TUV). MDAFs were
examined in terms of space (3 UK sites), time resolution (hourly to annual averages),
photolysis reactions (12 studied), optical inlet used (4-π sr and 2-π sr) and qualitative
impact on model chemical schemes. MDAFs derived from j(NO2) were found to be
seasonally similar around the UK, but specific to local environments at higher time resolutions, demonstrating the importance of local j-value measurements. Downwelling
(2-π) MDAFs demonstrated a slight increase with solar zenith angle (SZA), which was
amplified when measurements of upwelling j(NO2) were considered (4-π). Increased
surface albedo (snow cover) resulted in approximately 36% lower downwelling compared with 4-π MDAF, but the difference was negligible at other times. Derivations of
MDAF for the 12 different atmospheric photolysis reactions were grouped using hierarchical cluster analysis (HCA). The groupings of the photolysis reactions were found
to be driven by the extent to which a species photodissociates at longer (UVA) wave-lengths. MDAFs derived from j(NO2) measurements were deemed an applicable reference for local adjustment of the j-values for other photodissociations at wavelengths
>350 nm. For j-values of photodissociations at shorter wavelengths, adjustment using
MDAFs based on a reference of j(O1D) resulted in lower total error. The presence
of clouds had a greater influence on reducing cloud-free model results of j(NO2) (approx. 45%). Shorter wavelengths, such as those required for the photolysis rate constant
j(O1D), are scattered more readily in clear skies, and thus resulted in a lower magnitude difference (20%).
The other part of this PhD investigated atmospheric composition at the two UK supersites, by assessing the impact of the relocation of the southern EMEP supersite from
Harwell to Chilbolton Observatory, and deploying an iodide chemical ionisation mass
spectrometer (I – CIMS) to measure NOy species at the northern supersite (Auchencorth Moss). Meteorological normalisation was used on a concatenated time series of
pollutant concentrations pre- and post-relocation from Harwell to Chilbolton Observatory, to identify any resulting effects of the move on these time series. Of all the
species considered, only nitrogen oxides (NOx) and ammonia (NH3) had a step change
in concentration, both increasing. The additional contributing sources at Chilbolton
Observatory were identified. As a consequence, the long-term time series of NOx and
NH3 should be considered to be restarted following the relocation, and the new site not
strictly representative of the wider area it is intended to be. The aim of the CIMS study
at Auchencorth Moss was to measure HNO3 and N2O5 to quantify the interference in
co-located MARGA measurements, as well as to contribute the first Scottish ClNO2
measurements. The challenges of this study, and future work required is discussed.
This PhD research has demonstrated a new potential application of meteorological normalisation for air quality site relocations, which will become more pertinent in future
years where background sites will on occasion need to be relocated due to local development. Furthermore, this study has emphasised the importance of measuring local
photolysis rate constants to account for highly variable local conditions. It provides
discussion around making existing measurements standardised and accessible, so as to
make more frequent model validation or implementation of MDAF-like metrics easier,
and to improve modelled estimations of local photolysis rate constants without significantly increasing computational cost. This PhD research explores the ongoing need
to measure both atmospheric chemical components and photolysis rate constants to
understand changes in the atmosphere as pollutant emission abatement policies are implemented under real local conditions
Effect of workplace mobility on air pollution exposure and its inequality in the UK
Full text linkA large number of epidemiological studies have identified air pollution as a major risk to human health. Short-term and long-term exposures to air pollutants such as PM2.5, NO2 and O3 cause cardiovascular and respiratory diseases, cancer and other adverse health effects. These lead to decreased quality of life, increased hospital visits and premature mortality. Due to a high spatial and temporal variability of air pollution exposure, exposure inequalities exist within the society. Published studies suggest that it is often the most deprived and susceptible who are disproportionately exposed to the highest concentrations of some of the most ubiquitous air pollutants.
However, most epidemiological and exposure studies do not take into account the spatio-temporal variability of air pollutants and population mobility within their assessments which is likely to lead to exposure misclassification and, consequently, a bias in the associated health effects. Several modelling approaches have been developed to improve estimates of population exposure. Either statistical or deterministic models are now commonly used to predict air pollution concentrations. Deterministic models include atmospheric chemistry transport models (ACTMs), which tend to be used for larger study areas on a regional or higher scale, and Gaussian dispersion models, which on a local – urban – scale are able to predict concentrations at very high spatial resolutions. The aim of this thesis is to investigate how workplace-related population mobility and spatio-temporal variability of air pollution affect population exposure and its inequality in the UK.
Firstly, the effect of exposure to ambient air pollution at the place of work or study on overall population exposure in the UK is examined using publicly available data from Census 2011. The analysis is conducted for the whole of the UK (England, Wales, Scotland and Northern Ireland), and separately for Scotland only. The residential population distribution and daytime population distribution data are combined with concentration fields of key air pollutants (PM2.5, NO2 and O3) generated by the EMEP4UK atmospheric chemistry transport model at relatively high spatial (approximately 1.5 km × 2 km) and temporal (hourly) resolutions to calculate population exposure of stay-at-home ‘static’ population and a ‘dynamic’ population which spends a proportion of time on weekdays at the place of work or study. The calculated exposures of static and dynamic populations are compared, and sensitivity studies of different working hours of the dynamic population are conducted. The highest difference between dynamic and static population exposures is observed for NO2 (0.28 µg m-3 or 2.0% increase in the UK, 0.29 µg m-3 or 23.1% increase in Scotland) for working hours between 08:00 and 18:00. The calculated differences for PM2.5 and O3 are much smaller. Whilst at the population level the exposure difference is small, a case study using virtual individuals suggests a potential large variation between individuals.
Secondly, the exposure of dynamic population and population subgroups to air pollution is examined in a case study of the Central Belt of Scotland region. Additionally, the two largest and demographically contrasting urban areas within the region – Glasgow and Edinburgh – are considered separately. For the analysis, anonymised personal data of the participants of the Scottish Longitudinal Study (SLS), which is a representative sample of the Scottish population, are linked at the postcode unit level with air pollution concentrations generated by EMEP4UK (approximately 0.8 km × 1.4 km spatial resolution). The SLS participants are stratified by age, ethnicity and socio-economic status (SES) for the population subgroup exposure assessment. Exposures at residential address and the place of work or study are considered using three different work pattern scenarios and the results are compared with exposures of the ‘static’ population. Exposure gradients are observed across all demographic characteristics. Young people between 21 and 30 years of age tend to have the highest exposure to NO2 and PM2.5, and lowest to O3; however, those aged 31 to 50 tend to be most affected by inclusion of exposure at workplace. The patterns for SES and ethnicity are complex and study area specific; however, people in the two least deprived deciles consistently have the lowest residential and residential-workplace exposure to NO2 and PM2.5 but tend to see the highest increase in exposure due to workplace mobility. Overall, including exposure at place of work in exposure estimates tends to alleviate some of the exposure inequalities observed in the static population exposure assessments.
Thirdly, the effect of using different air pollution models on ‘dynamic’ population exposure estimates and its inequalities is investigated. The city of Edinburgh is chosen as the study area. Two models are considered: EMEP4UK and a Gaussian plume dispersion model, ADMS Urban. Detailed traffic emission data for all major and some minor roads in the city, and gridded emissions from other sources, are used in the ADMS Urban modelling. The model output is verified against available monitoring data. Differences in modelled output are observed between the models which are subsequently translated into differences in population exposure estimates. The effect of workplace exposure on overall population exposure to NO2 is larger for the ADMS-Urban model than for the EMEP4UK model; however, the magnitude is still very small (≤ 1.6%). For O¬3 and PM2.5, the effects are smaller and largely comparable between the models. With some notable exceptions, both models show similar patterns in both exposure inequality and the influence of workplace mobility on it.
Lastly, the overall findings and their implication for assessment of exposure and exposure inequality are discussed. This work suggests that inclusion of the place of work or study in exposure assessments makes only a small difference for population-scale burden assessment, particularly for those pollutants with secondary contributions such as O¬3 and PM2.5. This conclusion is not particularly sensitive to the atmospheric chemistry/dispersion model used
A chronology of ratios between black smoke and PM10 and PM2.5 in the context of comparison of air pollution epidemiology concentration-response functions
Full text linkBackground: For many air pollution epidemiological studies in Europe, ‘black smoke’ (BS) was the only measurement available to quantify ambient particulate matter (PM), particularly for exposures prior to the mid-1990s when quantification via the PM10 and/or PM2.5 metrics was introduced. The aim of this work was to review historic BS and PM measurements to allow comparison of health concentration-response functions (CRF) derived using BS as the measure of exposure with CRFs derived using PM10 or PM2.5. Methods: The literature was searched for quantitative information on measured ratios of BS:PM10, BS:PM2.5, and chemical composition of PM; with specific focus on the United Kingdom (UK) between 1970 and the early 2000s when BS measurements were discontinued. Results: The average BS:PM10 ratio in urban background air was just below unity at the start of the 1970s, decreased rapidly to ≈ 0.7 in the mid-1970s and to ≈ 0.5 at the end of the 1970s, with continued smaller declines in the 1980s, and was within the range 0.2–0.4 by the end of the 1990s. The limited data for the BS:PM2.5 ratio suggest it equalled or exceeded unity at the start of the 1970s, declined to ≈ 0.7 by the end of the 1970s, with slower decline thereafter to a range 0.4–0.65 by the end of the 1990s. For an epidemiological study that presents a CRF BS value, the corresponding CRF PM10 value can be estimated as R BS:PM10 × CRF BS where R BS:PM10 is the BS:PM10 concentration ratio, if the toxicity of PM10 is assumed due only to the component quantified by a BS measurement. In the general case of some (but unknown) contribution of toxicity from non-BS components of PM10 then CRF PM10 > R BS:PM10 × CRF BS, with CRF PM10 exceeding CRFBS if the toxicity of the other components in PM10 is greater than the toxicity of the component to which the BS metric is sensitive. Similar analyses were applied to relationships between CRF PM2.5 and CRF BS. Conclusions: Application of this analysis to example published CRF BS values for short and long-term health effects of PM suggest health effects from other components in the PM mixture in addition to the fine black particles characterised by BS
Development and application of low-cost monitoring approaches for atmospheric ammonia, acid gases and ammonium aerosols
Full text linkAmmonia (NH3) is the major alkaline gas in the atmosphere, with around 90 % of the total anthropogenic emissions in Europe coming from agriculture-related sources. Following emission to the atmosphere, the neutralisation reaction
between NH3 and the acid gases sulfur dioxide (SO2), nitric acid (HNO3) and hydrochloric acid (HCl) produces secondary inorganic aerosols (ammonium nitrate (NH4NO3), ammonium sulfate ((NH4)2SO4) and ammonium chloride (NH4Cl)). With longer atmospheric lifetimes than the gases, the aerosols also contribute to transboundary pollution problems. The gases and aerosols are removed from the atmosphere by wet (in precipitation) or dry (direct uptake by vegetation and surfaces) deposition processes. Together, they can negatively impact the natural environment through the input of excess acidity and nutrient nitrogen and harm human health through the formation of aerosols that contributes to fine-mode particulate matter (PM2.5). They can also potentially influence climate change from the radiative forcing properties of the aerosols and the inputs of nitrogen that can alter the carbon cycle.
Monitoring data are necessary for assessing the spatial and temporal extent of pollution and as evidence to detect changes in pollutant concentrations in response to current and future policies to mitigate emissions of NOx, SO2 and
NH3. Combined with models, the concentration data are also used to estimate the different fractions of the total sulfur or nitrogen input and different chemical forms of the pollutants. Since the spatial and temporal patterns and
atmospheric behaviours of gases and aerosols differ, measurements therefore need to distinguish between the phases.
The development of simple, low-cost, time-integrated air sampling methods and their application in cost-efficient monitoring strategies to assess temporal, spatial and trends in the gas and aerosol pollutants in the UK and across
Europe is described. An active diffusion denuder method (DELTA®) and a passive sampler (ALPHA®) are implemented at a large number of sites (> 70) in the UK National Ammonia Monitoring Network (NAMN, established 1996) to measure NH3 with a monthly frequency. An extension of the DELTA® method provided additional, monthly measurements of particulate NH4+(for the NAMN)and of the acid gases (SO2, HNO3, HCl) and aerosol species (NO3-, SO42-, Cl-,Na+, Ca2+, Mg2+) for the UK Acid Gas and Aerosol network (AGANet, established 1999) at a subset of NAMN sites. The close integration of the two
networks demonstrated the cost-effectiveness of the DELTA® approach, which provided quality assured, concurrent speciated measurement data on multiple pollutants at multiple sites, and also simplicity of operation by a large network of site operators, some of whom have no technical or scientific background. The DELTA® approach and quality protocol developed in the UK networks was further applied to a pan-European NitroEurope (NEU) DELTA® network (20 countries: 2006 – 2010), with knowledge sharing and collaboration between multiple laboratories and research organisations.
Important features in the spatial variability and seasonality in the gas and aerosol components were captured in the UK and European networks. The gases, with shorter lifetimes in the atmosphere were found to be spatially more
heterogeneous, with a wider range of concentrations than their aerosol counterparts. Variations on a spatial scale were correlated with distributions and magnitude of emission sources, e.g. NH3 and NH4+ concentrations were highest in intensively farmed areas (e.g. East Anglia in eastern England, NAMN) and countries (e.g. the Netherlands, NEU DELTA®). In the UK, evidence is also presented of the contribution by long-range transboundary sources to enhancement of concentrations of NH4NO3 and (NH4)2SO4.
Distinct and contrasting seasonal cycles in the gas and aerosol phase components were established, important for identifying periods of pollution and for targeting abatement measures. The observed variations were attributed to seasonal changes in emission sources, atmospheric interactions and the influence of climate on partitioning between the gases and aerosols. For NH3, peaks in concentrations occur from increased volatilisation promoted by warm, dry conditions (summer) and also from agriculture-related emissions, with a main peak in spring and a smaller peak in autumn. Concentrations of SO2 were higher concentrations in winter (increased combustion), except in Southern Europe where the peak period was in summer. HNO3 concentrations were more complex, with small peaks in the seasonal cycle related to traffic and industrial emissions, photochemistry, meteorology and the influence of climate
on HNO3:NH4NO3 equilibrium. In comparison, the springtime peak in NH4NO3 was attributed to the reaction of a surplus of NH3 with HNO3 to form NH4NO3 in the aerosol phase under cooler, wetter conditions. A summertime peak in particulate SO42- was observed in Southern Europe, coinciding also with peaks in SO2, NH3 and HNO3 concentrations. While the high HNO3 concentrations suggests increased oxidative capacity for formation of H2SO4 (from SO2) and reaction with NH3 to form (NH4)2SO4, the absence of an NH4+ peak illustrates
the larger influence of the more abundant NH4NO3 in controlling the seasonality of particulate NH4+.
Important changes in the atmospheric concentrations and partitioning between the different gas and aerosol components were captured. The measurement data highlighted the dominance of NH3 and NH4NO3 in rural air, as the
emissions of SO2 and NOx continues to fall, against a backdrop of increasing NH3 emissions in the UK and across Europe since 2013. The observed shift in the form of NH4
+ aerosol from the stable (NH4)2SO4 to the semi-volatile
NH4NO3 is expected to maintain a larger fraction of the NH3 and HNO3 in the gas phase. NH4NO3 can act as a reservoir and release the gases in warm weather, which may partly explain the observed non-linearity between emissions and measured concentrations of NH3 in the UK data. The current and projected trends in the emissions of the gases SO2, NOx and NH3 suggest that NH3 and NH4NO3 can be expected to continue to dominate the inorganic pollution load over the next decades
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