Spatio-temporal characteristics of PM10 concentration across Malaysia

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August–September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10–20 days quasi-biweekly (QBW) and 30–60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.     

Contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area, Portugal since the 19th century

The main purpose of this study was to evaluate the contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area (Portugal) since the 19th century. The study was based on pre-industrial and recent data series, the results being analyzed according to the atmospheric chemistry. The treatment of ozone and meteorological data was performed by classical statistics and by time-series analysis. It was concluded that in the 19th century the ozone present in the troposphere was not of photochemical origin, being possible to consider the respective concentrations as reference values. For recent data a cycle of 8h for ozone concentrations could be related to traffic. Compared to the 19th century, the current concentrations were 147% higher (252% higher in May) due to the increased photochemical production associated with the increased anthropogenic emissions.     

最小二乘支持向量机在臭氧浓度时间序列预测中试应用

将基于统计学理论的最小二乘支持向量机(LSSVM)方法试用于臭氧浓度时间序列预测.首先利用臭氧浓度时间序列资料重构了该混沌动力系统的相空间,然后沿着系统演化的相轨道用最小二乘支持向量机建立了臭氧浓度短时预测模型,并用上海市淀山湖站的臭氧观测资料做了提前1～8 h和提前24 h预报试验,结果显示这一模式能够较好地模拟臭氧浓度演化轨迹,提前1～8 h的预测精度均超过90%,提前24 h预报精度亦都在68%以上,预报效果较好.     

Estimation of in-use steel stock for civil engineering and building using nighttime light images

To establish a sustainable society, it is necessary to understand the flows and stocks of materials. However, traditional material flow analysis requires large quantities of data relating to the consumption and trade of materials in the past and the lifetime distributions of end use. To overcome the problem that such data may not be available, we have proposed using nighttime light images to estimate the in-use stocks of materials in countries for which the data are unavailable. In the previous study, in-use steel stock for civil engineering and building in 2006 was estimated using nighttime light images. However, several aspects of the methodology must be improved, and time-series analyses using nighttime light images have not yet been performed. Therefore, in this study, we improved the estimation of in-use steel stock by using new geological information (i.e., LandScan population distribution data) and correcting the pixel area. We prepared radiance-calibrated nighttime light data for 2006 and 2010 and conducted time-series analyses of the in-use steel stock using the nighttime light data. The in-use steel stock for civil engineering and building in 2010 was found to amount to approximately 11.3 Gt, which was approximately 21% higher than that in 2006.     

Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting

Introduction: COVID-19 has disrupted daily life and societal flow globally since December 2019; it introduced measures such as lockdown and suspension of all non-essential movements. As a result, driving activity was also significantly affected. Still, to-date, a quantitative assessment of the effect of COVID-19 on driving behavior during the lockdown is yet to be provided. This gap forms the motivation for this paper, which aims at comparing observed values concerning three indicators (average speed, speeding, and harsh braking), with forecasts based on their corresponding observations before the lockdown in Greece. Method: Time series of the three indicators were extracted using a specially developed smartphone application and transmitted to a back-end platform between 01/01/2020 and 09/05/2020, a time period containing normal operations, COVID-19 spreading, and the full lockdown period in Greece. Based on the collected data, XGBoost was employed to identify the most influential COVID-19 indicators, and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models were developed for obtaining forecasts on driving behavior. Results: Results revealed the intensity of the impact of COVID-19 on driving, especially on average speed, speeding, and harsh braking per 100 km. More specifically, speeds were found to increase by 2.27 km/h on average compared to the forecasted evolution, while harsh braking/100 km increased to almost 1.51 on average. On the bright side, road crashes in Greece were reduced by 49% during the months of COVID-19 compared to the non-COVID-19 period.     

Tourism effects on the environment and economic sustainability of sub-Saharan Africa

This paper integrates tourism, economic growth, and environmental issues in a multivariate format. Unlike recent research on this topic, a panel data of selected sample nations of sub-Saharan Africa is adopted by using cointegration and panel regression models. The current research discovers both long-run equilibrium and short-run dynamics between economic growth, tourism, energy use, and carbon emissions in sub-Saharan Africa. Furthermore, tourism and energy use show a highly significant direct impact on economic growth. In addition, tourism, energy use, and economic growth yield a highly significant positive effect on carbon emissions. Dissecting the region into oil producers and non-oil producers further suggests that the economic growth of sub-Saharan Africa has been accomplished by strong growth in tourism and energy use. However, there is highly significant evidence that in oil producing countries, CO₂ emissions are directly affected by energy use and economic growth and not by tourism. For non-oil producing countries, tourism and energy use but not economic growth incur a highly significant positive impact on carbon emissions.     

Estimation of Southeast Asian rice paddy areas with different ecosystems from moderate-resolution satellite imagery

Multi-temporal satellite imagery from the Moderate Resolution Imaging Spectrometer (MODIS) was used to map the different ecosystems of Southeast Asian (SEA) rice paddies. The algorithm was based on temporal profiles of vegetation strength and/or water content, using MODIS surface reflectance in visible to near-IR range. The results obtained from the analysis were compared to national statistics. Estimated SEA regional rice area was 42 × 10⁶ ha, which agrees with published values. The model performance was dependent on rice ecosystems. Good linear relationships between the model results and the national statistics were observed for rainfed rice. High linear coefficients of determination, R², were also found for irrigated rice and upland rice, but the model tended to underestimate irrigated rice and overestimate upland rice. However, these high R² values indicated that the model effectively simulated spatial distribution of these rice areas. These R² values were either of similar magnitude or larger than those reported in literature, regardless of the rice ecosystem. Poor correlation was observed for deepwater rice.     

Estimation of waste from computers and mobile phones in Iran

The amount of waste electrical and electronic equipment (WEEE) has been rapidly growing in recent years. Estimation close to reality of the future amounts of WEEE as a function of time is critical to effective their management. Wastes from mobile phones and computers are one of the several subgroups of WEEE. The objective of this study was to estimate past and future trends in the generation of obsolete computers and mobile phones in Iran. For this purpose a combination of two models were used. At the beginning, time-series multiple lifespan model was used to estimate outflows end-of-life obsolete equipment. Then, using the simplified logistic function model by Excel software, the values of obsolete computers and mobile phones in the future were estimated. The study found that the amount of E-waste generation in the country was 20 million wasted computers until 2016 and 39 million wasted mobile phones until 2014. Results of the time series model analysis showed a total amount of 2.8 million waste computers would be reused by 2016 and 4.2 million mobile phones would be reused by 2014. The results of the logistic equation indicate that by the year 2040 there will be 50 million units of obsolete computers. According to the same model 90 million mobile phones will be obsolete by 2035. Increase in the number of computers and mobile phones was fitted into the logistic model and the results showed that the saturation level of generation of obsolete computers and mobile phones are 24 and 21 years respectively following the base year 2016 and 2014.     

Meta-analysis of the Chinese studies of the association between ambient ozone and mortality

To investigate short-term effects of ambient ozone exposure on mortality in Chinese cities, we conducted a meta-analysis of 10 effect estimates of 5 short-term studies, which reported associations between ambient ozone and mortality in Chinese mainland cities. And we estimated pooled effects by non-accidental mortality, cardiovascular mortality, and respiratory mortality. Combined estimates and their 95%CI were tested by RevMan 5, and Funnel plots were used for the bias analysis. For a 10 μg m⁻³ increase of maximum 8-h average concentration of ozone, the percent change for non-accidental mortality, cardiovascular mortality, and respiratory mortality were 0.42 (95%CI, 0.32–0.52%), 0.44% (95%CI, 0.17–0.70%) and 0.50% (95%CI, 0.22–0.77%), respectively. Compared with pooled estimates from other meta-analyses on ambient ozone-associated mortality, our pooled estimate for non-accidental mortality was slightly higher than previous ones and pooled estimate for cardiovascular mortality was consistent with others. However, we observed significantly positive association between ambient ozone and respiratory mortality, which were generally nonsignificant in earlier studies. By combining estimates from published evidence, a small but substantial association between ambient ozone level and mortality was observed in Mainland China.