Net effect of air pollution controls on health risk in the Beijing-Tianjin-Hebei region during the 2022 winter Olympics and Paralympics

Due to the non-linearity in ozone(O_(3))formation,reducing the emission of nitrogen oxides(NO_(x))may increase O_(3) concentration.Given the counteractive O_(3) response to NO_(x) reduction,overall impact of air pollution controls can be ambiguous when the assessments focus on the changes in pollutant concentrations.In this study,a risk-based method was used to gauge the net effect of air pollution controls on mortality risk in the Beijing–Tianjin–Hebei(BTH)region during the 2022 Winter Olympics and Paralympics(WOP).This mega-event presents a unique opportunity to investigate the efficacy of deep cuts in pollutant emissions.Results show that O_(3) concentrations greatly increased as nitrogen dioxide(NO_(2))concentrations decreased in the BTH.Due to the active photochemical formations,O_(3) became the dominant pollutant that affected human health during the WOP.Despite the substantial O_(3) increases,the health benefits of NO_(2) reductions overwhelmed the adverse health effects of O_(3) increases in most regions of the BTH(at 81 out of 112 stations).After considering the impacts of particulate matter,the integrated health risk of air pollution mixtures declined almost everywhere in the BTH.Our results underscore the great necessity of changing the assessment paradigm of pollution control from using concentration-based methods to using risk-based methods.Together with the carbon neutrality policy,stringent control of NO_(x)emission from combustion sources is a promising way to achieve synergistic control solutions for air pollution and climate change.

Tracking Source Variations of Inhalation Cancer Risks and Ozone Formation Potential in Hong Kong over Two Decades(2000−2020)Using Toxic Air Pollutant Monitoring Data

Toxic air pollutants(TAPs)are a class of airborne chemicals known or suspected to cause serious health issues.This study,applying positive matrix factorization and inhalation unit risk estimates of TAPs,quantifies the changes in significant sources contributing to inhalation cancer risks(ICRs)from 2000 to 2020 in Hong Kong,China.Total ICR decreased from 1701 to 451 cases per million between 2000−2004 and 2016−2020,largely attributed to the reduction in diesel particulate matter(DPM),gasoline and solvent use-related volatile organic compounds(VOCs),and coal/biomass combustion-related polycyclic aromatic hydrocarbons and metal(loid)s.The regional contribution of VOCs associated with industrial and halogenated solvent sources increased substantially,representing the largest non-DPM ICR contributor(37%)in 2016−2020,stressing the need for a more comprehensive risk evaluation across the fast-growing and densely populated Greater Bay Area(GBA).ICRs in Hong Kong and the GBA will likely remain over 100 cases per million by 2050.The contributions to ozone formation potential of VOC/carbonyl sources were quantified,which show a notable shift from being solvent/gasoline-dominant in 2000−2004 to being more evenly shared by various sources in 2016−2020.Establishing a similar TAP monitoring network in the GBA is anticipated to provide the monitoring data needed to facilitate the development of more informed air quality management strategies.

Long-term variation and evaluation of air quality across Hong Kong region

Study of Air Quality Objectives(AQOs)and long-term changes of air pollution plays a decisive role in formulating and refining pollution control strategies.In this study,10-year variations of six major air pollutants were analyzed at seven monitoring sites in Hong Kong region.The continuous decrease of annual averaged concentrations of NO_(2),SO_(2),CO,PM_(2.5)and PM_(10)and numbers of days with severe pollution conditions validated the efficiency of the series of air pollution control schemes implemented by the Hong Kong region government.However,there is still a big gap to meet the ultimate targets described by the World Health Organization.Besides,the concentration of O_(3)at roadside and urban stations increased by 135%±25%and 37%±18%from 2011 to 2020,respectively,meanwhile the highest 8 hr averaged O_(3)concentration was observed as 294μg/m^(3)at background station in 2020,which pointed out the increasing ozone pollution in Hong Kong region.There was a great decrease in the annual times of air quality health index(AQHI)laying in“high”,“very high”and“serious”categories from 2011 to 2020 with the decrease rate of 89.70%,91.30%and 89.74%at roadside stations,and 79.03%,95.98%and 72.73%at urban stations,respectively.Nevertheless,the number of days categorized as“high”or above at roadside station was twice more than that in the urban station during the past ten years.Thus,more policies and attentions should be given to the roadside air quality and its adverse health effect to pedestrians on street.

Deep learning analysis of smart meter data from a small sample of room air conditioners facilitates routine assessment of their operational efficiency

Room air conditioners (RACs) are crucial household appliances that consume substantial amounts of electricity. Their efficiency tends to deteriorate over time, resulting in unnecessary energy wastage. Smart meters have become popular to monitor electricity use of home appliances, offering underexplored opportunities to evaluate RAC operational efficiency. Traditional supervised data-driven analysis methods necessitate a large sample size of RACs and their efficiency, which can be challenging to acquire. Additionally, the prevalence of zero values when RACs are off can skew training. To overcome these challenges, we assembled a dataset comprising a limited number of window-type RACs with measured operational efficiencies from 2021. We devised an intuitive zero filter and resampling protocol to process smart meter data and increase training samples. A deep learning-based encoder–decoder model was developed to evaluate RAC efficiency. Our findings suggest that our protocol and model accurately classify and regress RAC operational efficiency. We verified the usefulness of our approach by evaluating the RACs replaced in 2022 using 2022 smart meter data. Our case study demonstrates that repairing or replacing an inefficient RAC can save electricity by up to 17 %. Overall, our study offers a potential energy conservation solution by leveraging smart meters for regularly assessing RAC operational efficiency and facilitating smart preventive maintenance.

Measurement of heterogeneous uptake of NO2 on inorganic particles, sea water and urban grime

Heterogeneous reactions of NO2 on different surfaces play an important role in atmospheric NOxremoval and HONO formation,having profound impacts on photochemistry in polluted urban areas.Previous studies have suggested that the NO2 uptake on the ground or aerosol surfaces could be a dominant source for elevated HONO during the daytime.However,the uptake behavior of NO2 varies with different surfaces,and different uptake coefficients were used or derived in different studies.To obtain a more holistic picture of heterogeneous NO2 uptake on different surfaces,a series of laboratory experiments using different flow tube reactors was conducted,and the NO2 uptake coefficients(γ)were determined on inorganic particles,sea water and urban grime.The results showed that heterogeneous reactions on those surfaces were generally weak in dark conditions,with the measuredγvaried from<10-8 to 3.2×10-7 under different humidity.A photo-enhanced uptake of NO2 on urban grime was observed,with the obvious formation of HONO and NO from the heterogeneous reaction.The photo-enhancedγwas measured to be 1.9×10-6 at 5%relative humidity(RH)and 5.8×10-6 at 70%RH on urban grime,showing a positive RH dependence for both NO2 uptake and HONO formation.The results demonstrate an important role of urban grime in the daytime NO2-to-HONO conversion,and could be helpful to explain the unknown daytime HONO source in the polluted urban area.

Data-driven integrated assessment of global wild-caught seafood exported to Hong Kong by 2030 in different representative concentration and shared socioeconomic pathways

Wild-caught seafood is an important commodity traded globally.As elimate change and socioeconomic development is affecting global marine capture fisheries,the impact on regional supply remains unexplored,especially for areas like Hong Kong relying on global trading to meet high seafood consumption.However,it is challenging to assess the global marine capture fisheries production using complex process-based models.In this study,a data-driven integrated assessment approach was developed to evaluate the change of global seafood supply from wild catch.With the catch data available from 1990 to 2014,machine learning models were trained and tested including environmental,socioeconomic,geographic,and technological features to estimate the catch by ocean grid cells for individual species.Nine popular seafood categories in Hong Kong were studied,which include 68 species in total.Important input features for estimating the catch were compared across species and the impacts of these input features were interpreted using partial dependence plots.The global marine wild catch of the 68 species by countries and the export to Hong Kong were projected by 2030 in RCP2.6-SSPi,RCP4.5-SSP2,RCP7.0-SSP3,and RCP8.5-SSP5.Performances of machine learning models demonstrate the reliability of data-driven methods to estimate the catch by ocean grid cells.The importance of geographic features rank top for the estimate while that of climate change and socioeconomic development varies significantly across species.The projection reflects a drop of squid exported to Hong Kong due to the reduction of squid supply from China's mainland during 2015-2019.The export of wild-caught seafood of the nine categories to Hong Kong willhave a slight decline by about 16%from the 2020 level by 2030.The projection also suggests no significant differences among the four climatic-socioeconomically interrelated scenarios regarding the export to Hong Kong before 2030.Top producers include China's mainland,United States,and Japan.However,China's mainland and Japan will suffer from the decline.The data-driven integrated assessment approach can be improved to provide more insights into the long-term change and sustainable management.

Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data

Traditional air quality data have a spatial resolution of 1 km or above, making it challenging to resolve detailed air pollution exposure in complex urban areas. Combining urban morphology, dynamic traffic emission, regional and local meteorology, physicochemical transformations in air quality models using big data fusion technology, an ultra-fine resolution modeling system was developed to provide air quality data down to street level. Based on one-year ultra-fine resolution data, this study investigated the effects of pollution heterogeneity on the individual and population exposure to particulate matter(PM_(2.5)and PM_(10)),nitrogen dioxide(NO_(2)), and ozone(O_(3)) in Hong Kong, one of the most densely populated and urbanized cities. Sharp fine-scale variabilities in air pollution were revealed within individual city blocks. Using traditional 1 km average to represent individual exposure resulted in a positively skewed deviation of up to 200% for high-end exposure individuals. Citizens were disproportionally affected by air pollution, with annual pollutant concentrations varied by factors of 2 to 5 among 452 District Council Constituency Areas(DCCAs) in Hong Kong, indicating great environmental inequities among the population. Unfavorable city planning resulted in a positive spatial coincidence between pollution and population, which increased public exposure to air pollutants by as large as 46% among districts in Hong Kong. Our results highlight the importance of ultra-fine pollutant data in quantifying the heterogeneity in pollution exposure in the dense urban area and the critical role of smart urban planning in reducing exposure inequities.

An atmospheric water harvester with fast and energy-saving water removal and recovery

Moisture removal and water recovery from the air are vital for regulating indoor humidity and mitigating water scarcity.Most atmospheric water harvesters(AWH)focus primarily on increasing the moisture capture rate,but for it to be economical and sustainable,it is essential to consider the energy required to recover and harvest the captured water.Here,a mechanically flexible,biphilic sorption-based AWH made of green,environmentally friendly material is presented.It consists of a hygroscopic chitosan polymer embedded within a flexible,hydrophobic silica xerogel that can harvest 86.3 g water/g chitosan at 97%relative humidity and 25℃reaching saturation after 30 days(i.e.2.88 g water/g chitosan/day).Roughly 88%of the sorbed moisture was recovered by mechanical squeezing(ca.0.020 MPa)within 150 s.Repeated water harvesting experiments and uniaxial compression tests demonstrate that chitosan-silica xerogel is durable for longterm operations,providing a fast,reliable,and sustainable moisture removal and water harvesting tool.

Size-resolved effective density of submicron particles during summertime in the rural atmosphere of Beijing, China

Particle density is an important physical property of atmospheric particles. The information on high time-resolution size-resolved particle density is essential for understanding the atmospheric physical and chemical aging processes of aerosols particles. In the present study, a centrifugal particle mass analyzer （CPMA） combined with a differential mobility analyzer （DMA） was deployed to determine the size-resolved effective density of 50 to 350 nm particles at a rural site of Beijing during summer 2016. The measured particle effective densities decreased with increasing particle sizes and ranged from 1.43 to 1.55 g/cm3, on average. The effective particle density distributions were dominated by a mode peaked at around 1.5 g/cm3 for 50 to 350 nm particles. Extra modes with peaks at 1.0, 0.8, and 0.6 g/cm3 for 150, 240, and 350 nm particles, which might be freshly emitted soot particles, were observed during intensive primary emissions episodes. The particle effective densities showed a diurnal variation pattern, with higher values during daytime. A case study showed that the effective density of Aitken mode particles during the new particle formation （NPF） event decreased considerably, indicating the significant contribution of organics to new particle growth.

A comparative study between ionic liquid coating and counterparts in bulk for toluene absorption

The structure-activity relationship(SAR)for toluene absorption and desorption in ionic liquids(ILs)has been investigated for seven commercial ILs in bulk and thin liquid layer.ILs with imidazolium cations of different alkyl chain lengths and a Hofmeister series of anions including[CH3COO],[I],[BF4],[HSO4],and[PF6]were included.Absorption capacity for toluene increases with increasing kosmotropicity of the cation and anion,while the absorption rate in bulk ILs is governed by viscosity and that in thin ILs layer by the oil-water partition coefficient(Kow).A regenerability coefficient(Rp)measures toluene desorption and IL regeneration.The release rate as measured by dRp/dt correlates well with the Kow and viscosity of the ILs and tx,the time required to completely desorb toluene is related to its ionic strength as measured from v(C2H)of the imidazolium cation.These properties are in turn governed by the kosmotropicity of the cation and anion pair forming the IL.