Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

The spectrum of this study was research on the closed hydroponic cultivation of netted melons (Cucumis melo L.) using coir substrate, analyzing the impact of this cultivation method on melon yield, fruit quality, and the efficiency of water and nutrient usage. The experimental results showed that the average fruit weight of the melons grown in a closed system was 71.4 g higher than that of the open system, and the fruit width was on average 0.2 cm larger, showing a statistically significant difference. However, there was no difference in the average sugar content of the fruit flesh and height. Although there is no substantial commercial difference, it is conjectured that the change in the macronutrients ratio in the irrigation has played a role in the statistically significant increase in fruit weight, which is attributed to changes in the crops' nutrient uptake concentrations. This necessitates further research for a more comprehensive understanding. In terms of the productivity of irrigation required to produce the fruit, applying the closed system resulted in an increase of 7.6 kg/ton compared to the open system, saving 31.6% of water resources. Additionally, in terms of nutrients, cultivating in a closed system allowed for savings of approximately 59, 25, 55, 83, 76, and 87% of N, P, K, Ca, Mg, and S, respectively, throughout the entire cultivation period. As the drainage was reused, the ratios of NO3 - and Ca2+ increased up to a maximum of 9.6 and 9.1%, respectively, while the ratios of other ions gradually decreased. In summary, these results suggest that closed hydroponic cultivation can effectively optimize the use of water and fertilizer while maintaining excellent fruit quality in melon cultivation.

본 연구는 해양산업시설에서 배출되는 위험·유해물질(Hazardous and Noxious Substances) 중 아연을 대상으로 국내 서식종을 기반 으로 한 독성시험을 수행하고, 그 결과를 활용하여 국내 실정에 맞는 아연의 해양 수질 준거치(Marine Water Quality Criteria)를 제안하였다. 시험생물은 국내 연근해에 분포하고 산업적으로 유용하며, 표준 시험방법이 존재하는 종을 우선으로 5개의 분류군(Algae, Rotifer, Crustacean, Mollusc, Fish)의 총 10종을 선정하여 독성시험을 수행하였으며, 급·만성비(Acute-Chronic Ratio) 산출을 위하여 무척추동물, 어류 분류군에 대한 만성독성시험을 수행하였다. 국내종 독성시험에서 산출된 독성값을 활용한 수질준거치는 US EPA의 CCC (Criterion Continuous Concentration) 산출 기준으로 9.56 ㎍/L, 호주/뉴질랜드의 산출 기준으로 15.50 ㎍/L 로 나타나 호주/뉴질랜드에서 권고하는 기준인 14.40 ㎍/L 와 유사하였다. US EPA 및 호주/뉴질랜드는 자국의 생태독성 데이터베이스(US EPA Ecotox Database, Australasian Ecotoxicology Database)를 보유하고, 신뢰도 높은 독성값들을 생성하여 수질 기준 및 산출 기준을 갱신하고 있다. 한편, 국내에서는 국내종 기반 급성 독 성값을 적용하고 있지만, 중요한 산출 지표인 급·만성비는 US EPA 또는 유럽의 결과값을 활용하여 해양 수질 준거치를 산출하고 있으며, 국내의 생태독성 자료 또한 제한적인 실정이다. 따라서, 국내 해양 서식종을 기반으로 한 지속적인 독성시험과 준거치 설정 체계를 확보하 여 국내 해양생물과 생태계를 보호할 수 있는 해양 수질 준거치 도출이 필요할 것으로 판단된다.

조류의 이상증식을 일으키는 새만금호 부영양화를 평가하기 위해 Carlson 지수를 적용하였다. 연구를 위해 2021년 월별로 새만 금호내 총 7개 정점에서 수질조사를 실시하였다. Chl.a의 농도는 동계에는 만경수계가 약간 높았고, 춘계와 하계에는 동진수계가 약간 높 게 나타났으나, 일부 시기를 제외하고는 전체적으로 호소 수질환경기준 3등급과 비슷하거나 낮은 농도를 나타내었다. COD는 만경수계와 동진수계 모두 하계와 추계에 호소 수질환경기준 4등급과 유사하거나 상회하는 수질을 나타내었다. TOC는 모든 지점에서 3등급 이내의 수질을 보였다. 총인 농도는 호수 수질환경기준 4등급을 초과하였고, 월별로는 1월과 강우 후 8월에 높게 나타났다. 수질인자간의 상관성 분석에서 염분 농도에 대한 유기물, 총인, 총질소의 상관성이 상대적으로 높게 나타나 배수갑문을 통한 해수유입과 상류 하천을 통한 담 수 유입에 의한 담수역, 기수역, 해수역의 수질 특징을 반영하고 있었다. 영양상태지수에 의한 새만금호의 부영양화 변동 특성을 보면, Chl.a와 SD, TN의 지수에서 부영양화 초기 단계의 수질을 보였으며, TP 지수의 경우 심각한 부영양화 상태를 나타내고 있었다. 수질인자 간 부영양화 지수의 크기는 모든 수계에서 TSI(TP) > TSI(TN) > TSI(SD) > TSI(CHL)의 순으로 나타났다. TSI(CHL)에 대한 TSI(TP) 및 TSI(SD)와의 편차를 2차원 평면으로 나타낸 사분면 분석 결과를 보면, 조류 성장에 대한 총인이 영향에서는 모든 수계에서 대부분의 총인 (TP)에 의한 제한적 영향은 나타나지 않았으며, 빛 감쇠에 영향을 미치는 인자는 외부로부터 유입되는 적은 입자상 물질에 의한 영향이 크게 나타나는 것으로 평가할 수 있다.

Yellow-fleshed "Sweet Gold" kiwifruit on Jeju Island were studied to examine how irrigation and soil moisture control affected changes in photosynthetic traits and fruit quality during fruit maturation (120 to 170 days after full bloom). Concerning photosynthetic characteristics, the photosynthetic rate decreased by 10-19%, stomatal conductance by 24-47%, and transpiration rate by 8-25%, when compared to conventional irrigation, as irrigation was reduced and soil moisture content decreased. Fruit weight showed a tendency to increase until harvest, and while a lower soil moisture content led to a less pronounced increase in fruit weight, this difference was not statistically significant. The dry matter rate exhibited a similar trend to the change in fruit weight. Sugar content demonstrated a continuous increase after 130 days, with lower irrigation amounts resulting in higher levels of sugar content due to decreased soil moisture. The Hue value (h°) exhibited a continuous decrease after 140 days from full bloom, correlating with declining soil moisture content. After 130 days from full bloom, soluble sugar content increased rapidly while starch content gradually decreased after 150 days from full bloom. However, with conventional irrigation, the increase in soluble sugar content tended to be less noticeable. This study confirmed that in yellow-fleshed ‘Sweet Gold’ kiwifruit, managing irrigation and soil moisture reduction during the ripening period can lead to decreased fruit weight but increased dry matter, sugar content, and expression of flesh color, ultimately enhancing fruit quality and expediting ripening.

Almost all of the water from agricultural dams located to the upper of the Yeongsan river is supplied as irrigation water for farmland and thus is not discharged to the main stream of the river. Also, most of the irrigation water does not return to the river after use, adding to the lack of flow in the main stream. As a result, the water quality and aquatic health of the river have become the poorest among the four major rivers in Korea. Therefore, in this study, several strategies for water quality improvement of the river were developed considering pollution reduction and flow rate increase, and their effect analysis was performed using a water quality model. The results of this study showed that the target water quality of the Yeongsan river could be achieved if flow increase strategies (FISs) are intensively pursued in parallel with pollution reduction. The reason is because the water quality of the river has been steadily improved through pollution reduction but this method is now nearing the limit. In addition, rainfall-related FISs such as dam construction and water distribution adjustment may be less effective or lost if a megadrought continues due to climate change and then rainfall does not occur for a long time. Therefore, in the future, if the application conditions for the FISs are similar, the seawater desalination facility, which is independent of rainfall, should be considered as the priority installation target among the FISs. The reason is that seawater desalination facilities can replace the water supply function of dams, which are difficult to newly build in Korea, and can be useful as a climate change adaptation facility by preventing water-related disasters in the event of a long-term megadrought.

The purpose of this study was to investigate the effects of sterilization, storage period and washing yuzu, according to the washing method, during the storage period. The results showed that the fungus size increased as the storage period increased, and no mold occurred in the yuzu washed with ozone water until 20 days. After 30 days of storage, a mold of 124.1±13.9 mm2 was observed. The no-treatment sample had a fungus of 814.5±72.8 mm2 in size on day 0 and the fungus the largest fungus was 6,362±636.7 mm2 on day 30. In the case of water treatment, the fungus was 286.4±31.5~4,836.4±484.6 mm2 in size. The results of the study confirmed that washing yuzu with ozone water has a sterilizing effect.

새만금호는 우리나라 최대의 인공호수로 호수의 수질은 갈수록 악화되어 가고 있어 호수의 특성에 맞는 새로운 수질관리 대 책이 필요하다. 이에 새만금호의 국가수질측정망 자료를 이용하여 통계분석 기법에 의한 새만금호의 시공간적 수질특성을 분석하였다. 수질항목간의 상관성에서 수온과 TP는 상관성이 있고, 염분과 TN, 그리고 pH와 COD가 상관성이 높았다. 그 외 항목들 간에는 낮은 상관 성을 나타내어 관련성이 낮았다. 주성분 분석을 이용한 새만금호의 공간적 수질특성을 보면, 크게 4개의 그룹으로 구분되었는데, 담수 영 향구역과 해수 영향구역, 해수와 담수가 혼합되는 중간 수역이 2개 그룹으로 구분되어 각각 다른 수질특성을 나타내었다. 주성분분석을 이용한 시간적 수질특성은 계절적으로 4가지 그룹으로 구분되었다. 그룹Ⅰ은 늦봄과 초여름에 해당되는 5, 6월이고, 그룹 Ⅱ는 계절적으 로 초봄(3, 4월)과 늦가을(11, 12월)에 해당되는 시기로 나타났으며, 그룹 Ⅲ은 낮은 수온에 의한 용존산소의 증가가 나타나는 계절인 겨울 철(1, 2월)의 수질 특성을 보였고, 그룹 Ⅳ는 하계(7, 8, 9, 10월) 성층의 발달로 저층 퇴적물의 높은 인농도와 하계 고수온의 상관성을 가지 는 그룹으로 구분되었다. 이는 새만금호가 인위적으로 조성된 호수로써 상류 만경강과 동진강의 유입 영향을 받는 것과 동시에 새만금 방조제에 설치된 가력과 신시갑문을 통한 외해수 유입의 영향을 받음으로써 수질의 변동요소가 달라진 것으로 평가된다. 새만금호의 목 표수질을 달성하기 위해서는 상류 유역의 오염원 관리 대책과 함께 새만금호의 수질관리 대책을 수립할 필요가 있다.

This study focused on using indirect filtration through riverbeds to produce high-quality drinking water. Data on water quality from a water intake facility(capacity 10,000 m3/day) and nearby rivers were collected over a three-year period. The average intake facility specifications were found to be a specific surface area of 58 balls/m2, a mean particle size of 24 mm, an inflow velocity of 2.2 cm/sec, and a burial depth of 5 m. The water quality improvement rate was assessed as grade Ia, surpassing the adjacent river’s water quality. Correlation analysis showed a weak correlation between opening ratio, Suspended Solid (SS), and Biochemical Oxygen Demand (BOD) compared to total coliforms and fecal coliforms. The correlation coefficient R value of SS was -0.614, BOD was –0.588, total coliforms -0.870, and fecal coliforms -0.958. The R value shows a negative value, which showed that the larger the opening rate, the lower the removal rate of water pollutants. The correlation coefficient R values according to the depth of burial were found to be BOD 0.914, SS-0.124, total coliforms 1.000, and fecal coliforms 0.866. The deeper the burial depth, the higher the removal rate of BOD and microbial groups.

급격한 산업화와 도시화로 인해 해양 오염이 심각해지고 있으며, 이러한 해양 오염을 실효적으로 관리하기 위해 수질평가 지수(Water Quality Index, WQI)를 마련하여 활용하고 있다. 하지만 수질평가지수는 다소 복잡한 계산과정으로 인한 정보의 손실, 기준값 변동, 실무자의 계산오류, 통계적 오류 등의 불확실성(uncertainty)을 내포하고 있다. 이에 따라 국내ㆍ외에서 인공지능 기법을 활용하여 수질평가지수를 예측하기 위한 연구가 활발히 이루어지고 있다. 본 연구에서는 해양환경측정망 자료(2000 ~ 2020년)를 활용하여 우리나 라 전 해역 즉, 5개의 생태구에 대한 WQI를 추정할 수 있는 가장 적합한 인공지능기법을 도출하기 위해 총 6가지의 기법(RF, XGBoost, KNN, Ext, SVM, LR)을 실험하였다. 그 결과, Random Forest 기법이 다른 기법에 비해 가장 우수한 성능을 보였다. Random Forest 기법의 WQI 점수 예측값과 실제값의 잔차 분석 결과, 모든 생태구에서 시간적 및 공간적 예측 성능이 우수한 것으로 나타났다. 이를 통해 본 연구에서 개발한 Random Forest 기법은 높은 정확도를 바탕으로 우리나라 전해역에 대한 WQI를 예측 가능할 것으로 사료된다.

The management of algal bloom is essential for the proper management of water supply systems and to maintain the safety of drinking water. Chlorophyll-a(Chl-a) is a commonly used indicator to represent the algal concentration. In recent years, advanced machine learning models have been increasingly used to predict Chl-a in freshwater systems. Machine learning models show good performance in various fields, while the process of model development requires considerable labor and time by experts. Automated machine learning(auto ML) is an emerging field of machine learning study. Auto ML is used to develop machine learning models while minimizing the time and labor required in the model development process. This study developed an auto ML to predict Chl-a using auto sklearn, one of most widely used open source auto ML algorithms. The model performance was compared with other two popular ensemble machine learning models, random forest(RF) and XGBoost(XGB). The model performance was evaluated using three indices, root mean squared error, root mean squared error-observation standard deviation ratio(RSR) and Nash-Sutcliffe coefficient of efficiency. The RSR of auto ML, RF, and XGB were 0.659, 0.684 and 0.638, respectively. The results shows that auto ML outperforms RF, and XGB shows better prediction performance than auto ML, while the differences between model performances were not significant. Shapley value analysis, an explainable machine learning algorithm, was used to provide quantitative interpretation about the model prediction of auto ML developed in this study. The results of this study present the possible applicability of auto ML for the prediction of water quality.

Urban areas in watersheds increase the impervious surface, and agricultural areas deteriorate the water quality of rivers due to the use of fertilizers. As such, anthropogenic land use affects the type, intensity and quantity of land use and is closely related to the amount of substances and nutrients discharged to nearby streams. Riparian vegetation reduce the concentration of pollutants entering the watershed and mitigate the negative impacts of land use on rivers. This study analyzes the data through correlation analysis and regression analysis through point data measured twice a year in spring and autumn in 21 selected damaged tributary rivers within the Han River area, and then uses a structural equation model to determine the area land use. In the negative impact on water quality, the mitigation effect of riparian vegetation was estimated. As a result of the correlation analysis, the correlation between the agricultural area and water quality was stronger than that of the urban area, and the area ratio of riparian vegetation showed a negative correlation with water quality. As a result of the regression analysis, it was found that agricultural areas had a negative effect on water quality in all models, but the results were not statistically significant in the case of urban areas. As a result of the model estimated through the structural equation, BOD, COD, TN, and TP showed a mitigation effect due to the accumulation effect of river water quality through riparian vegetation in agricultural areas, but the effect of riparian vegetation through riparian vegetation was found in urban areas. There was no These results were interpreted as having a fairly low distribution rate in urban areas, and in the case of the study area, there was no impact due to riparian forests due to the form of scattered and distributed settlements rather than high-density urbanized areas. The results of this study were judged to be unreasonable to generalize by analyzing the rivers where most of the agricultural areas are distributed, and a follow-up to establish a structural equation model by expanding the watershed variables in urban areas and encompassing the variables of various factors affecting water quality research is required.

본 연구는 Bacillus subtilis를 활용한 바이오플락 양식 기술(Biofloc technology, BFT)을 이용하여 대농갱이(Leiocassis ussuriensis) 양식의 가능성을 확인하기 위해 90일 동안 생존, 성장지수와 사육수 수질의 변화를 관찰하였다. 대농갱이를 입식하기 전 BFT 수 제조를 위해 실험수조에 사료와 당밀을 첨가한 후 B. subtilis를 접종하여 40일간 수질을 안정화시켰다. 실험결과, 대농 갱이의 생존율은 대조구 92.7±3.2%와 BFT 실험구 95.8±3.3%로 조사되었다. 증체율은 대조구 118.1±9.0%와 BFT 실험구 197.7±15.6%을 보였고, 일간 성장율은 대조구 0.87±0.5%, BFT 실험 구 1.21±0.06%로 나타났다. 사료효율은 대조구가 43.7±2.6%이었고, BFT 실험구는 70.1±4.1%로 측정되어 BFT 실험구의 사료효율이 더 높은 것으로 조사되었다. 실험기간 동안의 수질 변화를 측정한 결과, pH는 대조구와 BFT 실험구 모두 감소되었고, MLSS는 대조구에서 변화를 보이지 않았지만, BFT 실험구에서는 90일째부터 유의한 증가를 보였다. NH4 +-N와 NO2 --N는 대조구 에서 실험 30일째부터 유의한 증가를 보였으나, BFT 실험구에서는 변화를 보이지 않았다. 결론 적으로 B. subtilis를 활용한 BFT 시스템을 대농갱이 양성 과정에 적용한 결과, 수질은 안정화 되는 경향을 보였고, 성장도와 사료효율은 대조구에 비해 높은 것으로 조사되어 긍정적인 효 과가 있는 것으로 확인되었다.

본 연구는 ‘암기조생’ 감귤 과실의 표면온도와 일사량 간의 상관관계를 분석하여 일소가 유발되는 과실 표면온도를 예측 하고 일소 발생을 경감시키고자 수행하였다. 이를 위해 기온 이 31℃일 때 30분 간격으로 5분 미세살수와 1% 탄산칼슘, 4% 카올린 용액을 10일 간격으로 3회 엽면살포하여 일소과 발생과 과실 품질을 조사하였다. 과실 표면온도는 일사량과 R = 0.788(p < 0.01)로 유의한 정의 상관관계를 나타냈으며 한 낮에는 기온보다 최고 16℃가 높았다. 과실 표면온도를 추정 하는 회귀식 y = 0.099 × (대기온도) + 0.018 × (일사량) + 20.779(R = 0.687, p < 0.01)을 도출하였다. 30분 간격으로 5 분 미세살수시 수관 내부 온도가 무처리보다 5.1℃ 낮았다. 일 소과 발생률은 미세살수구가 2.1%로 무처리구보다 2배 이상 낮았고 통계적으로 유의성을 나타냈으나, 과실 품질은 처리 간에 비슷하였다. 햇빛을 반사하거나 미세살수를 실시하여 과실 표면온도를 낮추면 일소 발생을 줄일 수 있을 것으로 보 인다.

본 연구에서는 하수 재이용을 위한 역삼투막 공정에서 전처리 정밀여과막(MF) 손상에 대한 누출되는 다양한 수 질변화로써 막 손상 검지 방안을 제시하였다. 이를 위하여 역삼투막 유입수질 적합성 평가지표인 SDI (silt density index)를 3에서 5의 범위 내에서 막 손상 시 검지 감도를 정량화하기 위하여 전처리 분리막이 1에서 3가닥 파단에 따라 SDI는 1.92에 서 6.11까지 증가한 결과를 확인할 수 있었다. 일반적으로 3을 기준으로 역삼투막 유입수질로 설정하였을 때 분리막이 3가닥 까지 파단이 되어야만 막 손상 검지가 가능하다는 것을 의미하며 역삼투막의 오염은 잠재적으로 가속화되어 효율을 저하시 킬 수 있다. 또한 이때 누출되는 입자성과 유기물질에 대하여 0.45 μm 이상의 크기만 걸러주는 입자계수는 입도분포별 막 파 단 개수에 따라 일정한 패턴을 확인할 수 없었으며, TOC 농도는 약 2배의 변화패턴으로써 SDI와의 상관관계로써 TOC가 막 손상 수질지표로써 신뢰성이 높은 것으로 확인되었다. 수질분석결과와 더불어 USEPA에서 제시하는 막 손상 검지 방법 중 압력손실시험과 이를 기반으로 LRVDIT 모델의 적합성 평가를 한 결과 막 손상 또는 역삼투막 공정으로 유입되는 막오염물질 을 신속하게 확인할 수 있는 SDI 및 TOC를 포함한 LRVDIT 모니터링과 UCL 설정을 병행해야 한다.

Benthic macroinvertebrates are important ecological and environmental indicators as primary or secondary consumers, and therefore are widely used in the evaluation of aquatic environments. However, there are no comprehensive river ecosystem monitoring surveys that link the major physicochemical water quality items with benthic macroinvertebrates in urban streams. Therefore, this study investigated the distribution characteristics of benthic macroinvertebrates and physicochemical water quality items (17 items) in Yangjaecheon and Yeouicheon from 2019 to 2020. At the same time, by applying Spearman’s rank correlation analysis and nonmetric multidimensional scaling (nMDS) analysis in the water quality data and biotic index, we tried to provide basic data for diagnosing the current status of river ecosystems in major urban rivers in Seoul. Based on the study results, a total of 39 species and 3,787 individuals were identified in Yangjaecheon, the water quality (based on BOD, TOC, and TP) of Yangjaecheon was higher than Grade Ib (good), and the BMI using benthic macroinvertebrates appeared as Grade C (normal) at all the sites. In Yeouicheon, a total of 51 species and 4,199 individuals were identified, the water quality (based on BOD, TOC, TP) was higher than Grade Ib (good) similar to Yangjaecheon, and the BMI of both Upstream and Saewon bridge was Grade B (good), while Yeoui bridge was Grade C (normal). Overall, analysis results for the distribution of benthic macroinvertebrates by a nonmetric multidimensional scaling method showed no significant difference between the two streams (p=0.1491). Also, significant environmental variables related to benthic macroinvertebrates distribution were determined as water temperature and DO. On the other hand, the results of the correlation analysis between biotic index and major water quality items confirmed that R1 and BMI could be used for on-site urban river water quality evaluation.

Understanding the characteristics of reservoir water quality is fundamental in reservoir ecosystem management. The water quality of reservoirs is affected by various factors including hydro-morphology of reservoirs, land use/cover, and human activities in their catchments. In this study, we classified 83 major reservoirs in South Korea based on nine physicochemical factors (pH, dissolved oxygen, chemical oxygen demand, total suspended solid, total nitrogen, total phosphorus, total organic carbon, electric conductivity, and chlorophyll-a) measured for five years (2015~2019). Study reservoirs were classified into five main clusters through hierarchical cluster analysis. Each cluster reflected differences in the water quality of reservoirs as well as hydromorphological variables such as elevation, catchment area, full water level, and full storage. In particular, water quality condition was low at a low elevation with large reservoirs representing cluster I. In the comparison of eutrophication status in major reservoirs in South Korea using the Korean trophic state index, in some reservoirs including cluster IV composed of lagoons, the eutrophication was improved compared to 2004~2008. However, eutrophication status has been more impaired in most agricultural reservoirs in clusters I, III, and V than past. Therefore, more attention is needed to improve the water quality of these reservoirs.

Although airborne wear particles (AWPs) generated from wheel-rail contacts are the major source of particulate matter (PM) in subway systems, studies on reducing the generation of such particles in order to enhance air quality are extremely rare. Therefore, this study investigated the effect of applying water-lubricant (applying tap water) on improving air quality by reducing the mass concentration (MC) of AWPs from wheel-rail contacts at a train velocity of 73 km/h using a twin-disk rig. An optical particle sizer was used to measure the MC of particles with the diameter range of 0.3 μm~10 μm. The results showed that the generation trends regarding PM1, PM2.5, and PM10 were different for dry and water-lubricated conditions: all three PMs showed an increasing-decreasing trend with slip rate under dry conditions; however, they were almost constant with slip rate under water-lubricated conditions. The particle size distributions were also different for dry and water-lubricated conditions: the peak occurred in multi-modal with the largest peak at approximately 6 μm in diameter under dry conditions; whereas, the peak occurred in bi-modal with the largest peak at approximately 0.9 μm in diameter under water-lubricated conditions. In addition, MCs were mostly smaller under water-lubricated conditions than dry conditions except at approximately 0.9 μm in diameter. Applying water significantly decreased PM1~2.5 and PM2.5~10 by more than 95%. This caused a decrease in PM2.5 and PM10 by 48.1% and 78.5%, respectively. On the other hand, applying water increased PM0.3~1 (i.e., PM1) by 52.8%, possibly owing to the effect of water vapor and mineral crystals from tap water. Overall, these findings indicate that water-lubrication can improve air quality in subway systems by reducing the MC of APWs generated from wheel-rail contacts. This study may provide a reference for future studies seeking to improve air quality in subway systems by reducing AWPs generated from wheel-rail contacts by applying lubricants.