Air Pollution Exposure Based on Nighttime Light Remote Sensing and Multi-source Geographic Data in Beijing

Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored.In the present study,multi-source data were combined to map the distribution of the AQI and population data,and the analyze their pollution population exposure of Beijing in 2018 was analyzed.Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018.Using Luojia-1 nighttime light remote sensing data,population statistics data,the population of Beijing in 2018 and point of interest data,the distribution of the permanent population in Beijing was estimated with a high precision of 200 m×200 m.Based on the spatialization results of the AQI and population of Beijing,the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level(PWEL)formula.The results show that the southern region of Beijing had a more serious level of air pollution,while the northern region was less polluted.At the same time,the population was found to agglomerate mainly in the central city and the peripheric areas thereof.In the present study,the exposure of different districts and towns in Beijing to pollution was analyzed,based on high resolution population spatialization data,it could take the pollution exposure issue down to each individual town.And we found that towns with higher exposure such as Yongshun Town,Shahe Town and Liyuan Town were all found to have a population of over 200000 which was much higher than the median population of townships of51741 in Beijing.Additionally,the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same,with the peak value being in winter and the lowest value being in summer.The exposure intensity in population clusters was relatively high.To reduce the level and intensity of pollution exposure,relevant departments should strengthen the governance of areas with high AQI,and pay particular attention to population clusters.

Optimization and Process Design Tools for Estimation of Weekly Exposure to Air Pollution Integrating Travel Patterns during Pregnancy

A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.

Pollution Dispersion in Urban Street Canyons with Green Belts

In this study,numerical simulations were used to explore the effects of roadside green belt,urban street spatial layout,and wind speed on vehicle exhaust emission diffusion in street canyon.The diffusion of different sized particles in the street canyon and the influence of wind speed were investigated.The individual daily average pollutant intake was used to evaluate the exposure level in a street canyon microenvironment.The central and leeward green belts of the road were the most conducive to the diffusion of pollutants,while the positioning of the green belts both sides of a road was least conducive to the diffusion of pollutants.Pollutant levels increased with increasing canopy height,canopy width,and decreasing tree spacing,with optimal values of 12 m,7 m,and 0.4 H,respectively.This provides protection from pollution for low-rise residents and pedestrians.The results presented here can be used to improve the air quality of the street microenvironment and provide a basis for the renovation of old street buildings.

A comparative study of the effects of ventilation-purification strategies on air quality and energy consumption in Beijing,China

In countries suffering from heavy ambient air pollution,ventilation is a problem,as ventilation intakes outdoor air pollutants,such as particulate matter with an aerodynamic diameter less than 2.5 μm(PM_(2.5)),while removing indoor air pollutants.Thus,it is important to identify appropriate ventilation-purification strategies to build healthy indoor environments with low energy consumption.This study reports the comparison of two sets of strategies,i.e.,mechanical ventilation with filters and natural ventilation with indoor air cleaners,in respect to energy consumption and the PMzs and carbon dioxide(CO_(2))exposure of occupants in a typical apartment in Beijing,China.A dynamic mass balance model was employed to calculate the PM2.5 and CO_(2) exposure concentrations,while the energy consumption of heating and cooling was simulated with the Designer's Simulation Toolkit.It was found that natural ventilation with air cleaners provided lower PIVhs exposure compared with that of mechanical ventilation with filters;however,mechanical ventilation achieved a lower CO_(2) exposure concentration.The annual cooling,heating,and fan energy consumption of natural ventilation strategies are lower than those of mechanical ventilation strategies.With respect to natural ventilation,an infiltration rate of 0.3-0.4 h^(-1)was the preferred setting,which led to low PM23 and CO_(2) exposure with lower energy consumption.The basic requirements for controlling indoor PM2.5 could be met if the threshold is set at 25 pg/m3.The results provide guidelines on how to combine multiple ventilation purification strategies to improve indoor air quality with lower energy usage.

Toxic effects of wastewater from various phases of monosodium glutamate production on seed germination and root elongation of crops

To make a comprehensive assessment on mono-sodium glutamate(MSG)wastewater pollution,a pollution exposure experiment was carried out on the seed germination and root elongation of wheat,Chinese cabbage and tomato by using the wastewater discharged from different processing phases of MSG production.The results showed that there were significantly positive linear relationships between the inhibitory rates of wheat seed germination and root elonga-tion and the CODcr of the mother liquor scraps.The toxicity of MSG wastewater to the test crops was in the order of tomato>Chinese cabbage>wheat,indicating that tomato was the most sensitive to the wastewater,and could be considered as an ideal toxic bioindicator.The half-effect concentrations(IC50)based on the seed germination and root elongation of the test crops exposed to the wastewater discharged from various processing phases of MSG produc-tion was 22.0-32432 and 17.3-3320 mg/L,respectively.

On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies

In many air pollution health studies,the time-activity pattern of individuals is often ignored largely due to lack of data.However,a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation.Here,we showcase the potential of iPhone’s Significant Location(iSL)data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants.In this study,one subject carried an iPhone in tandem with a reference GPS tracking device for one month.The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently.Using GPS data as a reference,we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period.We found the iSL data accurately captured the time the subject spent in 16 microenvironments(i.e.locations the subject visited more than once),which was 93%of the time during the study period.The average error of time-weighted aerosol optical depth value,a surrogate of particle pollution,is only 0.012%.To explore the availability of iSL data among iPhone users,an online survey was conducted.Among the 349 surveyed participants,72%of them have iSL data available.Considering the popularity of iPhones,iSL data may be available for a significant portion of the general population.Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation.

Investigating the impact of air pollution on AMI and COPD hospital admissions in the coastal city of Qingdao,China

Air pollution has been widely associated with adverse effects on the respiratory and cardiovascular systems.We investigated the relationship between acute myocardial infarction(AMI),chronic obstructive pulmonary disease(COPD)and air pollution exposure in the coastal city of Qingdao,China.Air pollution in this region is characterized by inland and oceanic transportation sources in addition to local emission.We examined the influence of PM_(2.5),PM_(10),NO_(2),SO_(2),CO and O_(3) concentrations on hospital admissions for AMI and COPD from October 1,2014,to September 30,2018,in Qingdao using a Poisson generalized additive model(GAM).We found that PM_(2.5),PM_(10),NO_(2),SO_(2) and CO exhibited a significant short-term(lag 1 day)association with AMI in the singlepollutant model among older adults(>65 years old)and females,especially during the cold season(October to March).In contrast,only NO2 and SO2 had clear cumulative lag associations with COPD admission for females and those over 65 years old at lag 01 and lag 03,respectively.In the twopollutant model,the exposure-response relationship fitted by the two-pollutant model did not change significantly.Our findings indicated that there is an inflection point between the concentration of certain air pollutants and the hospital admissions of AMI and COPD even under the linear assumption,indicative of the benefits of reducing air pollution vary with pollution levels.This study has important implications for the development of policy for air pollution control in Qingdao and the public health benefits of reducing air pollution levels.