Experimental evaluation of the impact of ventilation on cooking-generated fine particulate matter in a Chinese apartment kitchen and adjacent room.

Cooking is one of the major contributors to indoor pollution. Fine particulate matter (PM2.5) produced during cooking commonly mix into adjacent rooms and elevates indoor PM2.5 concentrations. The risk of human exposure to cooking-generated PM2.5 is mainly related to the exposure duration and particulate matter (PM) concentration. The PM2.5 concentration is influenced by cooking methods and ventilation patterns. Range hoods and open windows are conventional strategies for lowering the concentration of cooking-generated particles. To decrease PM emissions, kitchen air supply systems have been proposed, providing alternative possibilities for kitchen ventilation patterns. The effects of cooking methods, air supply systems, range hoods, and windows on PM2.5 concentrations must be analyzed and compared. To understand and provide advice on reducing exposure to PM2.5 due to cooking activities, we measured the PM2.5 mass concentration in a kitchen and adjacent room during cooking. The identified factors, including cooking method, range hood use, window status, and air supply system, were varied based on orthogonal design. The delay time between the PM2.5 peak in the kitchen and that in the adjacent room was determined. The degree of exposure risk for cooking-generated PM2.5 was evaluated using the mean exposure dose. The results indicated that the mean PM2.5 mass concentration in the kitchen ranged from 22 to 2296 µg/m3. In descending order, the factors affecting the indoor PM2.5 concentration in the apartment studied were range hood use, cooking methods, window status, and air supply system. The PM2.5 peak in the adjacent room occurred 200-800 s later than that in the kitchen. Other conditions being constant in these experiments, the use of range hoods, air supply systems, and windows reduce exposure doses by 90%, 37%, and 51%, respectively. These research results provide insights for reducing human exposure to cooking-generated PM2.5.

Measuring methane emissions during the installation of residential and commercial natural gas meters in China.

Methane is a potent greenhouse gas that accounts for one-quarter of the world's radiative forcing. Methane emissions from the natural gas sector are prevalent throughout the natural gas (NG) chain. Studies have shown that methane emissions from post-meter uses of natural gas are vastly understated. A surge in the number of natural gas users, for example, would amplify the climate impact of methane emissions during the installation of natural gas meters. Thus, quantifying methane emissions during the installation of natural gas meters is critical in light of severe global climate change and urgent reduction targets. In this study, we used a mass balance approach to calculate methane emissions during the separate installation of 1444 residential natural gas meters and 51 commercial natural gas meters. Our results revealed the methane emission had a fat tail distribution. Specifically, the estimated mean methane emissions for household users were 0.008 (0.001-0.022) kg per household and 0.192 (0.013-0.816) kg per commercial user. Extrapolating these statistics to the whole of China, total emissions from 2007 to 2021 were 3.80 million metric tons (MMt) CH4, with an annual average of 0.25 MMt. Notably, in terms of economic development and population size, the provinces with the highest methane emissions were concentrated in the southeast. Our findings close a gap in measuring CH4 emissions in China across the natural gas chain and provide data to support the reduction targets set and the development of reduction technologies.

Temperature-dependent particle number emission rates and emission characteristics during heating processes of edible oils.

The goal of this research is to investigate the temperature-dependent emission rates of particle numbers and emission characteristics during oil heating. Seven regularly used edible oils were studied in a variety of tests to attain this objective. First, total particle number emission rates ranging from 10 nm to 1 µm were measured, followed by an examination within six size intervals from 0.3 µm to 10 µm. Following that, the impacts of oil volume and oil surface area on the emission rate were investigated, and multiple regression models were developed based on the results. The results showed that corn, sunflower and soybean oils had higher emission rates than other oils above 200 °C, with peak values of 8.22 × 109#/s, 8.19 × 109#/s and 8.17 × 109#/s, respectively. Additionally, peanut and rice oils were observed to emit the most particles larger than 0.3 µm, followed by medium-emission (rapeseed and olive oils) and low-emission oils (corn, sunflower and soybean oils). In most cases, oil temperature (T) has the most significant influence on the emission rate during the smoking stage, but its influence was not as pronounced in the moderate smoking stage. The models obtained are all statistically significant (P < 0.001), with R2 values greater than 0.9, and the classical assumption test concluded that regressions were in accordance with the classical assumptions regarding normality, multicollinearity, and heteroscedasticity. In general, low oil volume and large oil surface area were more recommended for cooking to mitigate UFPs emission.

Temperature-dependent particle mass emission rate during heating of edible oils and their regression models.

Particulate matter emitted by heated cooking oil is hazardous to human health. To develop effective mitigation strategies, it is critical to know the amount of the emitted particles. The purpose of this research is to estimate the temperature-dependent particle mass emission rates of edible oils and to develop models for source strength based on the multiple linear regression method. First, this study examined seven commonly used oils by heating experiments. The emission rates of PM2.5 and PM10 were measured, and the effects of parameters such as oil volume and surface area on the emission rates were also analysed. Following that, the starting smoke points (Ts') and aggravating smoke points (Tss') of tested oils were determined. The results showed that oils with lower smoke points had greater emission rates. Notably, the experiments performed observed that peanut, rice, rapeseed and olive oil generated PM2.5 much faster at 240 °C (2.22, 1.50, 0.82 and 0.80 mg/s, respectively, at the highest emission conditions) than that of sunflower, soybean, and corn oil (0.15, 0.12 and 0.11 mg/s, respectively). The temperature, volume, and surface area of oils all had a significant impact on the particle mass emission rate, with oil temperature being the most influential. The regression models obtained were statistically significant (P < 0.001), with the majority of R2 values greater than 0.85. Using sunflower, soybean and corn oils, which have higher smoke points and lower emission rates, and smaller pans for cooking is therefore recommended based on our research findings.

Triglyceride-glucose index is a predictive index of hyperuricemia events in elderly patients with hypertension: a cross-sectional study.

BACKGROUND: To analyze the association between triglyceride-glucose index (TYG index) and hyperuricemia (HUA) in elderly patients with hypertension. METHODS: A total of 428 inpatients with primary hypertension from March 2018 to March 2021 in Qinghai Provincial People's Hospital were retrospectively analyzed. Grouped by sex and serum uric acid. Serum uric acid (SUA), fasting blood glucose (FPG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), urea nitrogen (BUN), triglycerides (TG), high-sensitivity C-reactive protein (HS-CRP) and other biochemical indicators were measured, and the TYG index was calculated. The TYG index and SUA levels of each group were compared, and the correlation between TYG index and hyperuricemia was analyzed. Multivariate Logistic regression was performed to analyze the relationship between TYG index and the risk of HUA in elderly patients with hypertension. The ROC curve was used to evaluate the predictive value of TYG index in elderly patients with hypertension associated with HUA. RESULTS: TYG index was significantly higher in the HUA group than in the normal group in both men and women (P < .05). Spearson correlation analysis showed that TYG index positively correlated with TC, TG, FPG, SUA, and LDL-C(r = 0.327, 0.975, 0.412, 0.214, 0.215, P = .000, 0.000, 0.000, 0.000, 0.000), and negatively correlated with age and HDL-C (r = -0.166, -0.248, P = .001, 0.000). Logistic regression analysis showed that Scr, BUN, HS-CRP and TYG index were the risk factors for HUA in elderly patients with hypertension (P < .05).The ROC curve showed an area under the TYG exponential curve of 0.617(95%CI:0.561 ~ 0.673) with a sensitivity of 64.4% and a specificity of 57.4%. CONCLUSION: TYG index in elderly hypertensive patients is closely related to hyperuricemia, and the increase of TYG index is an independent risk factor for HUA in elderly hypertensive patients.

A high triglyceride glucose index is associated with early renal impairment in the hypertensive patients.

Objective: Serum ß2-microglobulin (ß2-MG) and serum cystatin C (CysC) are sensitive and reliable indicators of early renal impairment. Triglyceride glucose index (TyG) is an emerging vital indicator of insulin resistance and is associated with increased risk of hypertension. We aimed to analyze the relationship between TyG and early renal impairment in hypertensive patients. Methods: A retrospective analysis was performed on 881 hypertensive patients treated in Qinghai Provincial People, s Hospital from March 2018 to March 2021, their clinical data and corresponding laboratory index values were recorded, and the TyG index was calculated. According to the TyG index, the patients were divided into a low TyG (L-TyG) group (TyG ≤ 8.50, n=306), medium TyG (M-TyG) group (8.51≤TyG ≤ 8.94, n=281), and high TyG (H-TyG) group (TyG>8.95, n=294) in sequence by using tertiles. Then, according to serum ß2-MG and CysC levels, they were divided into a normal renal function group (ß2-MG ≤ 2.4 mg/L, n=700 and CysC ≤ 1.25mg/L, n=721) and a renal function injury group (ß2-MG>2.4 mg/L, n=181, and CysC>1.25 mg/L, n=160). Multivariate linear regression analysis was used to analyze the influencing factors of serum ß2-microglobulin and cystatin C. Multivariate Logistic regression was used to analyze the relationship between the TyG index and early renal impairment in hypertensive patients. The receiver operating characteristic curve (ROC) was used to determine the value of the TyG index in predicting early renal impairment in patients with hypertension. Result: As the TyG index level increased, serum ß2-MG and CysC levels also gradually increased. Multivariate linear regression analysis showed that TyG index was the influencing factor of serum ß2-MG (B=0.060, P=0.007) and serum CysC (B=0.096, P<0.001). For every 1 standard deviation increase in the TyG index, the serum ß2-MG and CysC increased by 0.06mg/L and 0.096mg/L, respectively. When compared to the normal group, the TyG level (8.91 ± 0.65 vs 8.64 ± 0.60, P<0.001) was higher in the renal impairment group with ß2-MG>2.4 mg/L. The results of multivariate logistic regression analysis revealed that for every 1 standard deviation increase in the TyG index, the risk of early renal impairment in hypertensive patients increased 1.53 times (OR=1.53, 95%CI 1.006-2.303).The ROC curves showed that the TyG index was not superior to TG in predicting early renal impairment in hypertensive patients. the AUC values were 0.623 and 0.617, respectively. Then, when CysC>1.25 mg/L was used as the renal damage group, the level of TyG was still higher than that in the normal group (8.94 ± 0.67 and 8.64 ± 0.60, P<0.001). Multivariate Logistic regression analysis showed that for every 1 standard deviation increase in the TyG index, the risk of early renal impairment in hypertensive patients increased 2.82 times (OR=2.82, 95%CI 1.863-4.262). The ROC curves showed that the TyG index was not superior to TG in predicting early renal impairment in hypertensive patients. the AUC values were 0.629 and 0.626, respectively. Conclusion: TyG index is an influential factor in serum ß2-MG and CysC levels. The elevated TyG index levels are closely associated with the occurrence and development of early renal impairment in hypertensive patients, but it should be used cautiously in the prediction of early renal impairment.

PM2.5 mass concentration variation in urban residential buildings during heating season in severe cold region of China: A case study in Harbin.

Recent years, people pay great attention to fine particle matter (PM2.5) in indoor environment due to its negative impacts on health. Household cooking and severe air pollutant aggravate indoor PM2.5 level, especially during heating season in severe cold region of China. To find the variation of actual household PM2.5 influenced by both cooking activities and penetration from outdoor environment, a field measurement of PM2.5 concentrations in living room of residential buildings was conducted in Harbin, China. Firstly, six households in urban residence were selected to monitor the indoor PM2.5 mass concentration sequentially. Simultaneously, outdoor PM2.5 concentrations, temperature and indoor occupants' behavior were collected. Secondly, indoor to outdoor (I/O) ratios of PM2.5 in each household during monitoring campaigns were calculated. Influence of cooking activities and outdoor penetration on indoor PM2.5 concentrations in living room were also analyzed. Thirdly, some discussions were done for explanation of variation of PM2.5 in urban residential buildings. Results showed that the average PM2.5 mass concentrations varied from 11.7 to 48.6 µg/m3 indoor, while average I/O ratio value ranged from 0.33 to 1.23. Cooking in kitchen had significant impact on PM2.5 mass concentrations in living room, especially when frying, which could lead to peak value of 456.8 µg/m3 within 10 min from background level. Penetration led to the indoor PM2.5 level approximately 2 h behind with outdoor PM2.5 concentrations in general residences.

Indoor thermal environment and air quality in Chinese-style residential kitchens.

This paper reviews the published literature on indoor thermal environment and air quality in Chinese-style residential kitchens (CRKs). The paper first discusses typical characteristics of CRKs, including kitchen layout, cooking methods, and ventilation systems used. Next, the paper describes the current state of the indoor thermal environment and air quality in CRKs. Finally, this paper summarizes measures to control and improve the environment inside CRKs. The results indicate that the indoor environment of CRKs is too hot in summer and exhibits a large vertical temperature difference. No appropriate model was available for accurately evaluating the thermal environment in CRKs. At the same time, CRKs are highly polluted by COx, NOx, TVOC, and particulate matter (PM). Although existing exhaust hoods could improve the indoor environment to some extent, the use of a combined exhaust, make-up air, and air-conditioning system should be considered to provide a comfortable and healthy environment in CRKs.