Respirable Suspended Particulates Research Articles

Quantification of Indoor Respirable Suspended Particulate Matters (RSPM) and Asthma in Rural Children of Delhi-NCR.

To assess the exposure of indoor respirable suspended particulate matters (PM10, PM2.5, and PM1) and their association with asthma in children in a rural area of Delhi-NCR. It was a cross-sectional study. Fifty children with asthma from both biomass fuel users in group A and liquefied petroleum gas (LPG) fuel users in group B households were enrolled along with 50 healthy control subjects. The diagnosis of asthma was done as per the Global Initiative for Asthma (GINA), 2014. The 24-h levels of PM from all three groups of households were measured and compared. The level of PM with confounding factors like smoking and room occupancy was also compared between the groups. The 24-h concentrations of PM10, PM2.5, and PM1 were found significantly higher in the households of group A and group B as opposed to group C (p < 0.001). The number of smokers with a mean pack year and a lack of an exhaust fan was highest in group A and lowest in group C, while diesel and kerosene machines were highest in group B. The PMs were highest in group A even with different confounding factor (p < 0.001). The level of all PM was higher in group B than in group C, despite the presence of both types of fuel in group C households. The level of all PM was highest during the cooking hour. The level of 24-h PM was highest in group-A households. However, the level of PM was higher in group-B households than group C despite the presence of biomass fuel users in group C. This may be due to the higher number of smokers, poor room-occupancy and lack of exhaust fans.

A novel hybrid clustering model of region segmentation to fuse CMAQ simulations with observations

The Community Multiscale Air Quality (CMAQ) model can predict air pollutant concentrations at every pre-determined location but usually suffers from considerable systematic bias. By post-process the CAMQ simulations with ground observations, K-means-cluster-Observation-examiner-Boundary-denoiser (KOB) model was developed as an unsupervised hybrid model, to segment regions by capturing spatial dependencies of CMAQ time-series and systematically reduce the bias of CMAQ simulations. The KOB model was then applied in 2019 to improve the CMAQ predictions of respirable suspended particulates (RSP) concentrations in the Pearl River Delta (PRD) region of southern China. Compared to the CMAQ simulations, the KOB model is implemented with hourly CMAQ simulations and significantly improves the 1-h predictions of RSP at all stations, with the index of agreement (IOA) increasing from 0.70 to 0.86 and average root mean square error (RMSE) reducing from 28.4 to 20.0 μg/m3. A better agreement was also achieved between the monthly average RSP from predictions using the KOB model and ground observations, with IOA increased from 0.87 to 0.93 and RMSE decreased from 12.4 to 8.2 μg/m3. In addition, the capability of the KOB model to predict extreme pollution was greatly improved, with the RMSE reduced from 76.3 to 50.8 μg/m3. Furthermore, the improvement was identified not only for the next 1-h predictions, but also for the predictions in the next 6 h and after 6 h the SBC method outperforms the KOB model. Through data fusion, our hybrid clustering model can achieve robust real-time air quality forecasting.

A Study on Air Quality Index for Tiruchirappalli City Corporation

In recent years, Air quality monitoring and pollution control is a foremost environmental concern in the world. The World Health Organization estimates 14 million people are affected by air pollution every year. Respiratory and Heart related diseases are mostly caused by air pollutants. Tiruchirappalli is the fourth largest city in the state of Tamilnadu. The study was carried out during the months of December 2018 to March 2019. Ten locations were selected randomly for air quality analysis status for Tiruchirappalli city. The present study aims to develop air quality index, Sulphur Dioxide, Nitrogen Oxides, Respirable Suspended Particulate Matter and Suspended Particulate Matter. The study revealed that the Ariyamangalam area has higher air pollutants than other locations. PM10 and SPM exceeds the permissible limit of NAAQ Standards. SO2 and NOx within limit but continued exposure will lead to health hazards.

Collaborative environmental management for transboundary air pollution problems: A differential levies game

<p style='text-indent:20px;'>This paper develops a new cooperative dynamic time consistent model for studying regional air pollution management issues in a cooperative game framework for formulating pollution control policies and dynamically consistent compensation mechanisms. As air pollution is a transboundary issue, unilateral response on the part of one region is generally ineffective. Regional cooperation is essential to resolve serious environmental problems. In addition, the long-term environmental impacts are closely related to the building up existing air pollution stocks in Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Respirable suspended particulates (RSP) and Ozone (O3). A cooperative dynamic game with different types of pollutants is developed. We characterize the non-cooperative outcomes, and examine the cooperative arrangements, group optimal actions, and individually rational imputations. In particular, an air pollution levy consisting of four components involving damage charges on emissions of sulfur dioxide, nitrogen dioxide, respirable suspended particulates and ozone depletion materials. Cooperative games offer the possibility of socially optimal and group efficient solutions to the lack of cooperation among different regions involving decision problems among strategic actors. This paper makes a valuable contribution to the literature as this is the first cooperative dynamic time consistent model for regional management of different types of air pollutants.

4946The effects of climate and air pollutants on heart failure hospitalizations and mortality (CLIMATE-HF Study)

Abstract Background The data on the effects of air pollution on acute heart failure (HF) in tropical countries is limited. Particulate matter air pollution in Thailand is comparably higher than in other countries in Southeast Asia. The existence of climate and air pollution seasonal variation in our country has never been studied before. Purposes We sought to explore the effects of air pollution on HF hospitalizations and in-hospital mortality, including the effects of seasonal variation on HF negative outcomes and the association between air pollutants and hospitalizations of acute heart failure across geographical areas. Methods We undertook a retrospective analysis of longitudinal collected clinical data. The Data from 258,539 patients with primary HF admissions and daily pollutant parameters between 2011 and 2015 were collected. Data in daily pollutant parameters including respirable suspended particulates with diameter ≤10 μm (PM10), total suspended particles, ozone, carbon monoxide, nitric oxide, sulfur dioxide, air quality index were obtained. Generalized additive regression models and non-linear distributed lag functions were performed. Results 440,988 hospital admissions occurred with strong seasonal variation and peaked in winter. Particulate matter ≤10 μm (PM10) 2 days prior to admission date was associated with relative risk (RR) (95% confidence interval (CI)) of 1.02 (1.00–1.04, p-value &lt;0.001) for HF hospitalizations after adjusting with age, sex, respiratory tract infection, acute coronary syndrome and other HF comorbidities (diabetes, hypertension, chronic kidney disease). The association of HF hospitalizations and seasonal PM10 variations was strongest in the Northeastern part of Thailand with RR (95% CI) of 1.04 (1.01–1.05), p-value = 0.005. Conclusion HF hospitalizations were associated with preceding PM10 exposure, especially in the area with greater seasonal PM10 variations. Reducing exposure to particulate matter air pollution among those at risk for HF may be the potential prevention of HF hospitalizations. Acknowledgement/Funding Research grant from Heart Failure Foundation, Ramathibodi Hospital

Projecting the impacts of atmospheric conditions under climate change on air quality over the Pearl River Delta region

Anthropogenic climate change has been increasingly confirmed by weather observation and scientific literature in recent decades. Atmospheric stability, which has strong effects on vertical mixing of air pollutants and thus air quality, may be affected under climate change. This study aims to statistically assess the impacts of climate change alone on the future air quality in the Pearl River Delta region in the near future (2030–2039) and the far future (2090–2099) under two Representative Concentration Pathways (RCP) scenarios, i.e., RCP 4.5 and RCP 8.5, based on the future surface and upper level meteorological data projected by one regional climate model (RCM): WRF, and by four general circulation models (GCMs): CanESM2, MIROC, MRI-CGCM3 and MPI-ESM-LR. The arithmetic means of projections reveal an increase in the levels of air pollutants [ozone (O3), respirable suspended particulates (RSP) and sulphur dioxide (SO2)] in various seasons, even though a decrease is projected to occur in June-July-August. These changes in projected mean concentration are more significant in the far future, and under the RCP8.5 scenario. Among difference meteorological variables, surface temperature is most associated with the projected change in the three pollutants, with a range from 56.9% to 65.2% in all seasons and for all pollutants, relative to all contributions in RCP8.5 for example. Other notable associations include positive effects of vertical temperature gradient and the temperature–dew point difference on pollutant concentration. We found an increase in frequency of high pollution levels in December–January–February and March–April–May, as the occurrence proportion of pollutant concentration greater than the recent 95th percentile is 9.5%–9.6% and 6.4%–9.2%, respectively. We conclude that climate change alone is projected to have significant effect on air quality in the Pearl River Delta region in future, implying the necessity of more stringent air pollutant emission control policies to mitigate air pollution in the future.

Assessing the impacts of seasonal and vertical atmospheric conditions on air quality over the Pearl River Delta region

Air pollution is an increasingly concerning problem in many metropolitan areas due to its adverse public health and environmental impacts. Vertical atmospheric conditions have strong effects on vertical mixing of air pollutants, which directly affects surface air quality. The characteristics and magnitude of how vertical atmospheric conditions affect surface air quality, which are critical to future air quality projections, have not yet been fully understood. This study aims to enhance understanding of the annual and seasonal sensitivities of air pollution to both surface and vertical atmospheric conditions. Based on both surface and vertical meteorological characteristics provided by 1994–2003 monthly dynamic downscaling data from the Weather and Research Forecast Model, we develop generalized linear models (GLMs) to study the relationships between surface air pollutants (ozone, respirable suspended particulates, and sulfur dioxide) and atmospheric conditions in the Pearl River Delta (PRD) region. Applying Principal Component Regression (PCR) to address multi-collinearity, we study the contributions of various meteorological variables to pollutants’ concentration levels based on the loading and model coefficient of major principal components. Our results show that relatively high pollutant concentration occurs under relatively low mid-level troposphere temperature gradients, low relative humidity, weak southerly wind (or strong northerly wind) and weak westerly wind (or strong easterly wind). Moreover, the correlations vary among pollutant species, seasons, and meteorological variables at various altitudes. In general, pollutant sensitivity to meteorological variables is found to be greater in winter than in other seasons, and the sensitivity of ozone to meteorology differs from that of the other two pollutants. Applying our GLMs to anomalous air pollution episodes, we find that meteorological variables up to mid troposphere (∼700 mb) play an important role in influencing surface air quality, pinpointing the significant and unique associations between meteorological variables at higher altitudes and surface air quality.

Trans-boundary air pollution in a city under various atmospheric conditions

Trans-boundary air pollution (TAP) is a crucial factor affecting air quality, and its contribution may vary over time and differ under various atmospheric conditions. This study firstly applies an integrated statistical scheme to estimate the contributions of TAP and local sources to air pollutants in a city, and then investigate the influences of tropical cyclones (TC) on TAP. Hong Kong is chosen as an example because of its significant and special TAP characteristics. This study focuses on four major air pollutants, namely, respirable and fine suspended particulates (RSP/PM10 and FSP/PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2), from 2002 to 2013. Our results show that, on average, TAP is the major contributor of the annual RSP, FSP, SO2, and NO2 in Hong Kong. We estimate that when a TC is approaching, the increase in pollutant concentration in Hong Kong is mainly due to the increase in TAP contribution by the strengthened northerly wind at higher level of atmosphere (≥900hPa). These changes are accompanied by decreases in precipitation and increases in northerly/north-easterly wind, which may prolong the lifetime of pollutants, enhancing pollutant transport from mainland China to Hong Kong.

Polluting Emissions in the City of La Paz, Mexico: Emissions Inventory and Monitoring Data

In the City of La Paz, Mexico, there is growing concern amongst the local population due to the uncertainty about the local air quality. To address this concern, an air pollutants emissions inventory was recently carried out as a first step to better understand air quality in La Paz. The inventory considers point, area, mobile and natural sources and it includes six major air pollutants: sulphur oxides (SOx), nitrogen oxides (NOx), respirable suspended particulates (RSP or PM10), fine suspended particulates (FSP or PM2.5), volatile organic compounds (VOC), and carbon monoxide (CO). The reference year for the inventory is 2013. This paper presents the main results of the inventory by source category. In addition, the local power utility maintains three air quality monitoring stations in the city. Data from these stations are also presented and analysed in this paper. Electricity generation and motor vehicles are the main emissions sources. The paper highlights the importance of having in place adequate emissions control systems and operations. Some recommendations for the local authorities include a ten-year air quality and emissions reduction plan that considers measures such as the imposition of statutory emission caps on power plants, implementation of renewable energies and mandatory annual roadworthiness and exhaust pipe emissions tests for on-road vehicles.

Evaluation of Indoor Air Quality Screening Strategies: A Step-Wise Approach for IAQ Screening.

Conducting a full indoor air quality (IAQ) assessment in air-conditioned offices requires large-scale material and manpower resources. However, an IAQ index can be adopted as a handy screening tool to identify any premises (with poor IAQ) that need more comprehensive IAQ assessments to prioritize IAQ improvements. This study proposes a step-wise IAQ screening protocol to facilitate its cost-effective management among building owners and managers. The effectiveness of three IAQ indices, namely θ1 (with one parameter: CO2), θ2 (with two parameters: CO2 and respirable suspended particulates, RSP) and θ3 (with three parameters: CO2, RSP, and total volatile organic compounds, TVOC) are evaluated. Compared in a pairwise manner with respect to the minimum satisfaction levels as stated in the IAQ Certification Scheme by the Hong Kong Environmental Protection Department, the results show that a screening test with more surrogate IAQ parameters is good at identifying both lower and higher risk groups for unsatisfactory IAQ, and thus offers higher resolution. Through the sensitivity and specificity for identifying IAQ problems, the effectiveness of alternative IAQ screening methods with different monitoring parameters is also reported.

Developing a statistical based approach for predicting local air quality in complex terrain area

A statistical framework has been developed for predicting the next-day air quality for Hong Kong. In this approach, Generalized Additive Models (GAMs) linking air pollutant concentration with meteorological data were first constructed, based on observations during the December 1997 to November 2009 period. GAMs were used for forecasting local air quality with weather predictions from (1) the Global Forecast System (GFS) model; (2) dynamical downscaling of GFS predictions using WRF model (GFS-WRF), and (3) bias corrected GFS-WRF (Improved GFS-WRF). The system was verified by carrying out retrospective daily air quality predictions in this one-year period (December 2009 to November 2010). Even with the uncertainties in weather predictions, it was found that, downscaled weather forecasts from Improved GFS-WRF combined with GAMs give better results than those based on GFS and GFS-WRF alone. The statistical model with Improved GFS-WRF inputs performed well in forecasting both urban and sub-urban pollutant concentrations including respirable suspended particulates, O3 and NO2. The Hit Rate (False Alarm Ratio) for categorical forecasts of events with daily air pollution index (API) over 100 given by Improved GFS-WRF is also higher (or possibly lower) than that using GFS and GFS-WRF only. Further, this paper describes the implementation of Improved GFS-WRF to detect the onset of O3 episodes in advance due to the presence of tropical cyclones, based on categorical evaluation and supported by case studies. Our results indicate that the statistical model can be a useful tool for air quality prediction for urban and sub-urban sites in the complex terrain area, like Hong Kong.

Forecasting PM10 in Algiers: efficacy of multilayer perceptron networks.

Air quality forecasting system has acquired high importance in atmospheric pollution due to its negative impacts on the environment and human health. The artificial neural network is one of the most common soft computing methods that can be pragmatic for carving such complex problem. In this paper, we used a multilayer perceptron neural network to forecast the daily averaged concentration of the respirable suspended particulates with aerodynamic diameter of not more than 10 μm (PM10) in Algiers, Algeria. The data for training and testing the network are based on the data sampled from 2002 to 2006 collected by SAMASAFIA network center at El Hamma station. The meteorological data, air temperature, relative humidity, and wind speed, are used as inputs network parameters in the formation of model. The training patterns used correspond to 41 days data. The performance of the developed models was evaluated on the basis index of agreement and other statistical parameters. It was seen that the overall performance of model with 15 neurons is better than the ones with 5 and 10 neurons. The results of multilayer network with as few as one hidden layer and 15 neurons were quite reasonable than the ones with 5 and 10 neurons. Finally, an error around 9% has been reached.

Prediction and Analysis of Dust Dispersion from Drilling Operation in Opencast Coal Mines

Dust is one of the most important air pollutants and is the major area of concern for coal mining industry, because opencast coal mining operations lead to the generation of large quantity of dust, which deteriorates the surrounding environment and the public health. Dust generation from several mining activities consists of PM2.5, PM10 and RespirableSuspended Particulates(RSP) concentrations. Any new project to be proposed should perform Environmental Management Plan (EMP) studies to predict the possible dust generation from that project. Presently USEPA models are used to predict dust concentration. An attempt is made to develop two mathematical models to predict the respirable dust particle concentration in the ambient air at various locations around the dust generating source, especially from drilling operation in Open Cast coal mines. The models were developed using different statistical tools. The required data has been generated by field investigations carried out at one of the opencast coal mines in southern India. The models were developed by providing meteorological data like wind speed, wind direction, relative humidity and temperature, the geographical data like distance from the dust source and emission rate of drilling operation as the input parameters. Results from these models were compared with USEPA model and the field measured values. Predicted values were found to be in close agreement with the Field Measured Values than USEPA model predicted values.

Spatial Patterns of Seasonal Level Diurnal Variations of Ozone and Respirable Suspended Particulates in Hong Kong

In this study we analyzed the diurnal spatial patterns of cycles of ozone (O3) and respirable suspended particulate (RSP) matter in Hong Kong between 2001 and 2011. We used harmonic analysis to reveal the diurnal cycle in the seasonal-level spatial patterns. The diurnal cycle of O3 is stronger in the northeast rural areas of Hong Kong than in the urban center due to the lower titration effects of nitric oxide in the rural areas. For RSP, the southern sections show the strongest diurnal cycle and the northeastern sections show the weakest diurnal cycle, which could be explained by the heavy vehicular traffic in the southern urban areas and light vehicular traffic in the northeast rural areas. The diurnal patterns of O3 and RSP both show stronger cycles in the summer months, which might be related to the diurnal rainfall pattern. The time of maximum for O3 is around 1400 Local Standard Time (LST) in the afternoon in summer, whereas a wider range in the time of maximum, between 1100 and 1400 LST, was observed in winter. The spatial pattern of the time of maximum for RSP showed a gradual progression from the center of the city to the west, between 1300 and 1700 LST, which is consistent with rush hour traffic.

Associations between mortality and meteorological and pollutant variables during the cool season in two Asian cities with sub-tropical climates: Hong Kong and Taipei

BackgroundNumerous studies have found associations between extreme temperatures and human mortality but relatively few studies have been done in sub-tropical and tropical cities, especially in Asia. In this study we examine the impact of cold temperatures, cold waves and other meteorological and environmental variables on cool season mortality in 2 subtropical Asian cities.MethodsSeparate analysis of daily mortality time-series from Hong Kong and Taipei using Generalized Additive Models with natural mortality as the outcome daily mean temperature as the main explanatory variable and relative humidity, solar radiation, wind speed, pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), respirable suspended particulates (PM10), ozone (O3), seasonality and day of the week controlled as potential confounders. Lags up to 35 days were considered for temperature, and distributed lag models were used to determine the number of lags for final models. Subgroup analyses were also done by gender, age group, cause of death and geographical area of residence.ResultsCold temperatures were strongly associated with higher mortality with lagged effects persisting up to 3 weeks in Hong Kong and 2 weeks in Taipei. Cold effects were much stronger for deaths among older people and non-cancer deaths. Prolonged cold spells modestly but significantly raised mortality after accounting for the effects of individual cold days. Higher daily ozone levels were also strongly associated with higher short-term mortality in Taipei and Hong Kong, while relative humidity and solar radiation were weakly and inconsistently associated with mortality.ConclusionsCold temperatures and cold spells substantially increase short-term mortality in sub-tropical Asian cities particularly among the elderly. Greater attention needs to be paid to the adverse health effects of cold temperatures. Interventions including provisions of shelters, cold weather warnings and education about the possible health effects of cold temperature should be carried out in sub-tropical areas.

Improvement of the multilayer perceptron for air quality modelling through an adaptive learning scheme

Multilayer perceptron (MLP), normally trained by the offline backpropagation algorithm, could not adapt to the changing air quality system and subsequently underperforms. To improve this, the extended Kalman filter is adopted into the learning algorithm to build a time-varying multilayer perceptron (TVMLP) in this study. Application of the TVMLP to model the daily averaged concentration of the respirable suspended particulates with aerodynamic diameter of not more than 10µm (PM10) in Macau shows statistically significant improvement on the performance indicators over the MLP counterpart. In addition, the adaptive learning algorithm could also address explicitly the uncertainty of the prediction so that confidence intervals can be provided. More importantly, the adaptiveness of the TVMLP gives prediction improvement on the region of higher particulate concentrations that the public concerns.

Emissions trading in Hong Kong and the Pearl River Delta region—A modeling approach to trade decisions in Hong Kong's electricity industry

Abstract In 2002, the Hong Kong government and the Guangdong provincial government agreed to reduce emissions of sulfur dioxide, nitrogen oxides, respirable suspended particulates, and volatile organic compounds by 40%, 20%, 55%, and 55%, respectively. There was strong public demand for the power stations in Hong Kong to reduce emissions. Emission caps were introduced, with allowances for the trading of emission credits. However, local power stations were using equipment built in the 1980s and 1990s, making it difficult for them to meet the new emissions requirements. The situation presented a new challenge, which involved a choice of either improving the existing equipment, or using emissions trading to meet the emission caps. This study reviews the background on emissions in Hong Kong and the surrounding regions, the “cap and trade” system, and the technologies used for power generation and emission reduction. A modeling approach is adopted to simulate the equipment, the electricity dispatching requirements, and the costs of either reducing emissions or trading emission credits. Data from a power station in Hong Kong was chosen for the simulation. Different options were simulated in the model to identify the optimal strategy. The results were then compared with the plan for emission reduction. This study demonstrates that a modeling approach using linear programming can analyze the complicated options involving emission reduction and investments to achieve an optimized business solution.

Differences Between Weekday and Weekend Levels of Ozone, NO2, NOx, and Respirable Suspended Particulates in Hong Kong

Abstract Differences in ozone (O3), nitrogen oxides (NOx), and respirable suspended particulate (RSP) weekday and weekend concentrations in Hong Kong were investigated. Data were collected hourly by the Hong Kong Environmental Protection Department from January 1999 to October 2007 at 14 sites: 9 urban, 4 newly developed, and 1 rural station. Weekend O3 concentrations were 14% and 22% higher for the afternoon peak O3 time and 8-h O3 average concentrations, respectively, at six urban stations, whereas NO2 and NOx concentrations were 19% and 25% lower, respectively, during the afternoon O3 peak time on weekends. No significant differences in peak afternoon O3 concentrations were found at the newly developed or rural stations. Weekend RSP concentrations were lower at most urban stations. Urban RSP concentrations were lower on weekends than weekdays, by 14% for the morning rush hour and 8% for the daily average RSP. O3 formation sensitivity to volatile organic compounds and lower weekend NOx emissions could e...

Assessing air quality in Hong Kong: A proposed, revised air pollution index (API)

The Environment Protection Department of Hong Kong has been using an air pollution index (API) to report the status of ambient air quality since 1995. Such an index system was first developed by the USA Environmental Protection Authority. The API compares five main air pollutants, i.e. sulfur dioxide (SO 2), respirable suspended particulates (RSP), nitrogen dioxide (NO 2), carbon monoxide (CO) and Ozone (O 3) as sub-indexes, which are calculated separately from a segmented linear function that transforms ambient pollutants concentrations into a normalized scale extending from 0 to 500. The resultant pollution level is described by the maximal value of these five sub-indexes. The limitation of this API system is that it considers only one pollutant with the maximum value at a time but reflects other pollutants concurrently. In this study, a revised air quality index (RAPI) is proposed based on the entropy function, which combines the effect of all pollutants on public health. The design of the revised index is based on database of air pollutants collected at two air quality monitoring stations in Hong Kong, i.e. a roadside station in Mong Kok and a general station in Sha Tin. Compared with the existing API, values of RAPI (calculated from data collected for API) at both stations are at higher levels and provide more information of levels of all pollutants. Therefore, RAPI should be representatively and widely used to provide the public with a better indicator of air quality. In addition, variations and oscillations of pollutants concentrations were also examined and the results show that RSP and NO 2 contribute more to the overall pollution level than other components. It is suggested that more abatement strategies be focused on these pollutants to improve air quality in the future.

Variations of respirable suspended particulates in Hong Kong: cross-boundary and local effects

Analysis of the spatial and temporal variability of respirable suspended particulates (RSP) observed in 11 Hong Kong general stations over the period 2000–2008 shows a high concentration in the northwest and low concentration in the southeast and coastal areas, with the central area in between. Seasonally, RSP concentration is highest in winter, followed by autumn, and is lowest in summer. A bimodal peak in diurnal cycle with peaks in the morning (7–8 a.m.) and early evening (6–7 p.m.) can be attributed to rush-hour traffic flows as well as local land–sea breeze circulations. The effect of vehicular emission is also demonstrated in a distinct weekly cycle, with a Sunday minimum. Analysis of RSP concentration for different wind directions shows the importance of cross-boundary transport of pollutants from the Pearl River Delta area, with 43% of noncompliant cases associated with cross-boundary transport. An empirical orthogonal function (EOF) analysis shows that the first EOF pattern of RSP changes is characterized by changes of the same sign for all 11 general stations, with the second pattern dominated by changes in the Yuen Long station. Time series analysis shows that changes in the second EOF leads the first, indicating that changes in Yuen Long (northwest) precede changes elsewhere. Stations located in the coastal area change last. Tap Mun shows significant increasing trends in RSP concentration, particularly for incidences of high RSP occurrences, which may be attributed to increases in shipping in the Yan Tian International Container Terminal. Raymond Kwok-Cheung Lok is currently affiliated with the HK Transport Department.