scholarly journals Understanding Spatial Variability of Air Quality in Sydney: Part 2—A Roadside Case Study

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 217 ◽  
Author(s):  
Imogen Wadlow ◽  
Clare Paton-Walsh ◽  
Hugh Forehead ◽  
Pascal Perez ◽  
Mehrdad Amirghasemi ◽  
...  
Keyword(s):  
Air Quality ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Subject Area ◽  
Traffic Model ◽  
Urban Landscapes ◽  
Study Region ◽  
Main Road ◽  
Agent Based ◽  
Clean Air

Motivated by public interest, the Clean Air and Urban Landscapes (CAUL) hub deployed instrumentation to measure air quality at a roadside location in Sydney. The main aim was to compare concentrations of fine particulate matter (PM2.5) measured along a busy road section with ambient regional urban background levels, as measured at nearby regulatory air quality stations. The study also explored spatial and temporal variations in the observed PM2.5 concentrations. The chosen area was Randwick in Sydney, because it was also the subject area for an agent-based traffic model. Over a four-day campaign in February 2017, continuous measurements of PM2.5 were made along and around the main road. In addition, a traffic counting application was used to gather data for evaluation of the agent-based traffic model. The average hourly PM2.5 concentration was 13 µg/m3, which is approximately twice the concentrations at the nearby regulatory air quality network sites measured over the same period. Roadside concentrations of PM2.5 were about 50% higher in the morning rush-hour than the afternoon rush hour, and slightly lower (reductions of <30%) 50 m away from the main road, on cross-roads. The traffic model under-estimated vehicle numbers by about 4 fold, and failed to replicate the temporal variations in traffic flow, which we assume was due to an influx of traffic from outside the study region dominating traffic patterns. Our findings suggest that those working for long hours outdoors at busy roadside locations are at greater risk of suffering detrimental health effects associated with higher levels of exposure to PM2.5. Furthermore, the worse air quality in the morning rush hour means that, where possible, joggers and cyclists should avoid busy roads around these times.

scholarly journals Contributions of Trans-boundary Transport to the Summertime Air Quality in Beijing, China

2016 ◽  
Author(s):  
Jiarui Wu ◽  
Guohui Li ◽  
Junji Cao ◽  
Naifang Bei ◽  
Yichen Wang ◽  
...  
Keyword(s):  
Air Quality ◽  
Control Strategies ◽  
Dominant Role ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Pollutant Emissions ◽  
Beijing China ◽  
Local Emissions ◽  
Factor Separation ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing-Tianjin-Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of emissions outside of Beijing to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the pure local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from pure emissions outside of Beijing. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions of local emissions with those outside of Beijing. The pure emissions outside of Beijing play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much more than 13.7 % from pure Beijing local emissions. The emissions interactions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is primarily determined by the trans-boundary transport of emissions outside of Beijing during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is a key for Beijing to improve air quality. Considering the uncertainties in the emission inventory and the meteorological field simulations, further studies need to be performed to improve the WRF-CHEM model simulations to reasonably evaluate trans-boundary transport contributions to the air quality in Beijing for supporting the design and implementation of emission control strategies.

scholarly journals Roadside Air Quality Forecasting in Shanghai with a Novel Sequence-to-Sequence Model

2020 ◽  
Vol 17 (24) ◽  
pp. 9471
Author(s):  
Dongsheng Wang ◽  
Hong-Wei Wang ◽  
Chao Li ◽  
Kai-Fa Lu ◽  
Zhong-Ren Peng ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Traffic Management ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Learning Ability ◽  
Observation Data ◽  
Deterministic Models ◽  
Co Concentrations ◽  
Air Quality Forecasting

The establishment of an effective roadside air quality forecasting model provides important information for proper traffic management to mitigate severe pollution, and for alerting resident’s outdoor plans to minimize exposure. Current deterministic models rely on numerical simulation and the tuning of parameters, and empirical models present powerful learning ability but have not fully considered the temporal periodicity of air pollutants. In order to take the periodicity of pollutants into empirical air quality forecasting models, this study evaluates the temporal variations of air pollutants and develops a novel sequence to sequence model with weekly periodicity to forecast air quality. Two-year observation data from Shanghai roadside air quality monitoring stations are employed to support analyzing and modeling. The results conclude that the fine particulate matter (PM2.5) and carbon monoxide (CO) concentrations show obvious daily and weekly variations, and the temporal patterns are nearly consistent with the periodicity of traffic flow in Shanghai. Compared with PM2.5, the CO concentrations are more affected by traffic variation. The proposed model outperforms the baseline model in terms of accuracy, and presents a higher linear consistency in PM2.5 prediction and lower errors in CO prediction. This study could assist environmental researchers to further improve the technologies for urban air quality forecasting, and serve as tools for supporting policymakers to implement related traffic management and emission control policies.

scholarly journals Contributions of residential coal combustion to the air quality in Beijing–Tianjin–Hebei (BTH), China: a case study

2018 ◽  
Vol 18 (14) ◽  
pp. 10675-10691 ◽  
Author(s):  
Xia Li ◽  
Jiarui Wu ◽  
Miriam Elser ◽  
Tian Feng ◽  
Junji Cao ◽  
...  
Keyword(s):  
Air Quality ◽  
Coal Combustion ◽  
Fine Particulate Matter ◽  
Clean Energy ◽  
Temporal Variations ◽  
Aerosol Mass ◽  
Haze Formation ◽  
Surrounding Areas ◽  
Residential Coal ◽  
Mass Concentrations

Abstract. In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing–Tianjin–Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30 % decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0 % on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields.

scholarly journals Contributions of residential coal combustion to the air quality in Beijing-Tianjin-Hebei (BTH), China: A case study

2018 ◽  
Author(s):  
Xia Li ◽  
Jiarui Wu ◽  
Miriam Elser ◽  
Junji Cao ◽  
Tian Feng ◽  
...  
Keyword(s):  
Air Quality ◽  
Coal Combustion ◽  
Fine Particulate Matter ◽  
Clean Energy ◽  
Temporal Variations ◽  
Haze Formation ◽  
Surrounding Areas ◽  
Residential Coal ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate contributions of the residential coal combustion (RCC) emission to the air quality in Beijing-Tianjin-Hebei (BTH) during persistent air pollution episodes from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the air pollutants mass concentrations are in good agreement with observations at monitoring sites in BTH. The WRF-CHEM model also reasonably well reproduces the temporal variations of aerosol species compared with the AMS measurements in Beijing. The RCC emission plays an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate PM2.5 from the RCC emission, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emission in BTH and its surrounding areas is excluded in simulations, with a 30 % decrease of PM2.5 concentrations. However, when only the RCC emission in Beijing is excluded, the Beijing's PM2.5 level is decreased by 18.0 % on average. Our results suggest that implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the Beijing's air quality, but is not expected to bring back the blue sky to Beijing. Should the residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies need be conducted considering the uncertainties in the emission inventory and meteorological fields.

scholarly journals Enhanced representation of soil NO emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

2016 ◽  
Vol 9 (9) ◽  
pp. 3177-3197 ◽  
Author(s):  
Quazi Z. Rasool ◽  
Rui Zhang ◽  
Benjamin Lash ◽  
Daniel S. Cohan ◽  
Ellen J. Cooter ◽  
...  
Keyword(s):  
Air Quality ◽  
Fine Particulate Matter ◽  
Model Performance ◽  
Temporal Distribution ◽  
Soil Parameters ◽  
N Availability ◽  
Ozone Monitoring Instrument ◽  
Generic Data ◽  
Clean Air ◽  
No Emissions

Abstract. Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

scholarly journals Contributions of trans-boundary transport to summertime air quality in Beijing, China

2017 ◽  
Vol 17 (3) ◽  
pp. 2035-2051 ◽  
Author(s):  
Jiarui Wu ◽  
Guohui Li ◽  
Junji Cao ◽  
Naifang Bei ◽  
Yichen Wang ◽  
...  
Keyword(s):  
Air Quality ◽  
Dominant Role ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Pollutant Emissions ◽  
Fine Particulate ◽  
Beijing China ◽  
Local Emissions ◽  
Factor Separation ◽  
Good Agreement

Abstract. In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing–Tianjin–Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of non-Beijing emissions to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from non-Beijing emissions. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions between local and non-Beijing emissions. The non-Beijing emissions play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much higher than 13.7 %, from Beijing local emissions. The emission interactions between local and non-Beijing emissions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is generally determined by the trans-boundary transport of non-Beijing emissions during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is key for Beijing to improve air quality.

On the issue of optimization of atmospheric air quality monitoring for the implementation of the Federal project «Clean Air»

2019 ◽  
pp. 931-936
Author(s):  
I. V. May ◽  
A. A. Kokoulina ◽  
S. Yu. Balashov
Keyword(s):  
Public Health ◽  
Air Quality ◽  
Environmental Monitoring ◽  
Monitoring System ◽  
Protection Measures ◽  
Atmospheric Air ◽  
Monitoring Programs ◽  
Clean Air ◽  
Effectiveness And Efficiency ◽  
The City

Introduction. The city of Chita of Zabaikalsky region is one of the cities of Russia, priority on level of pollution of atmosphere. Of the order of 130 impurities emitted by the sources of the city, 12 are monitored at 5 posts of the Roshydromet network. Maximum monthly average concentrations are formed by benz (a) pyrene (up to 56.8 MPC), hydrogen sulfide (12.3 MPC), suspended particles (up to 4PDC), phenol (up to 3.6 MPC). Significant emissions (59.73 thousand tons in 2018) are aggravated by the use of coal as a fuel by heat and power enterprises and the private sector, climatic and geographical features. Within the framework of the Federal project “Clean Air” of the national project “Ecology”, it is envisaged to reduce the gross emission of pollutants into the atmosphere of Chita by 8.75 thousand tons by 2024, which should lead to a significant improvement in the safety and quality of life of citizens. It is necessary to identify the most “risky “components of pollution for health.It is important to understand: whether the environmental monitoring system reflects the real picture of the dangers posed by pollution of the city’s atmosphere; whether there is a need to optimize the monitoring system for the subsequent assessment of the effectiveness and efficiency of measures; what impurities and at what points should be monitored in the interests of the population, administration and economic entities implementing air protection measures.The aim of the study is to develop recommendations for optimizing the program of environmental monitoring of air quality in the city of Chita, taking into account the criteria of danger to public health for the subsequent evaluation of the effectiveness and effectiveness of the Federal project “Clean Air”.Materials and methods. Justification of optimization of monitoring programs was carried out through the calculation of hazard indices, considering: the mass of emissions and toxicological characteristics of each chemical; the population under the influence. A vector map of the city with a layer “population density” was used as a topographic base. The indices were calculated for regular grid cells covering the residential area. For each cell, the repeatability of winds of 8 points from the priority enterprises and the population within the calculated cell were taken into account. As a result, each calculation cell was characterized by a total coefficient, taking into account the danger of potential impacts of emissions. Based on the results of the assessments, recommendations were formulated to optimize the placement of posts in the city and the formation of monitoring programs.Results. Indices of carcinogenic danger to the health of the population of Chita ranged from 584,805. 96 to 0.03 (priorities: carbon (soot), benzene, benz (a) pyrene); indices of non-carcinogenic danger — from 1,443,558. 24 to 0.00 (priorities: sulfur dioxide, inorganic dust containing 70–20% SiO2, fuel oil ash). The greatest danger to public health stationary sources of emissions form in the North-Western, Western and South-Eastern parts of the city. Roshydromet posts in these zones are absent.Conclusions. As part of the objectives of the project “Clean Air”, it is recommended to Supplement the existing state network of observations of atmospheric air quality in Chita with two posts; to include manganese, xylene, vanadium pentoxide in the monitoring programs, to carry out the determination of Benz(a)pyrene et all posts, which will allow to fully and adequately assess the danger of emissions of economic entities, as well as the effectiveness and efficiency of the provided air protection measures.

scholarly journals Simultaneous Monitoring of Particle-Bound PAHs Inside a Low-Energy School Building and Outdoors over Two Weeks in France

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 108
Author(s):  
Céline Liaud ◽  
Sarah Chouvenc ◽  
Stéphane Le Calvé
Keyword(s):  
Particle Size ◽  
Air Quality ◽  
High Performance ◽  
Sampling Period ◽  
Temporal Variations ◽  
Ventilation Rate ◽  
Low Energy ◽  
Total Particle ◽  
Polycyclic Aromatic ◽  
Individual Pahs

The emergence of new super-insulated buildings to reduce energy consumption can lead to a degradation of the indoor air quality. While some studies were carried out to assess the air quality in these super-insulated buildings, they were usually focused on the measurement of gas phase pollutants such as carbon dioxide and volatile organic compounds. This work reports the first measurements of Polycyclic Aromatic Hydrocarbons (PAHs) associated with particles as a function of time and particle size in a low-energy building. The airborne particles were collected indoors and outdoors over three to four days of sampling using two three-stage cascade impactors allowing to sample simultaneously particles with aerodynamic diameter Dae > 10 µm, 2.5 µm < Dae < 10 µm, 1 µm < Dae < 2.5 µm, and Dae < 1 µm. The 16 US-EPA priority PAHs were then extracted and quantified by high-performance liquid chromatography (HPLC) coupled to fluorescence detection. The resulting total particle concentrations were low, in the ranges 3.73 to 9.66 and 0.60 to 8.83 µg m-3 for indoors and outdoors, respectively. Thirteen PAHs were always detected in all the samples. The total PAH concentrations varied between 290 and 415 pg m−3 depending on the particle size, the environment (indoors or outdoors) and the sampling period considered. More interestingly, the temporal variations of individual PAHs highlighted that high molecular weight PAHs were mainly associated to the finest particles and some of them exhibited similar temporal behaviors, suggesting a common emission source. The indoor-to-outdoor concentration ratios of individual PAH were usually found close to or less than 1, except during the event combining rainy conditions and limited indoor ventilation rate.

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