Urban Climate最新文献

{"title":"Microscale urban heat variability and time-location patterns: Elevated exposure for bikers and rickshaw drivers beyond average city temperatures in megacity","authors":"","doi":"10.1016/j.uclim.2024.102177","DOIUrl":"10.1016/j.uclim.2024.102177","url":null,"abstract":"<div><div>Urban heat island effect creates diverse microclimates, influencing heat exposure and consequent health effects. Study measured heat exposure among delivery riders within their microclimate, comparing it with city's average temperature. We investigated how higher exposure affects work, health, and productivity of riders.</div><div>For 21 days in winter and summer, we measured heat exposure during peak hours (under sun and shade) in riders' immediate environment, at seven high-traffic routes in Karachi, Pakistan. Recorded temperature were compared with city's ambient air temperature. In-depth interviews were conducted to assess the impacts on riders' health, welfare, and productivity.</div><div>During winter, temperature was 5.0 °C higher under sun and 1.6 °C higher under shade, as compared to city average recorded temperatures. In summer temperature was 5.5 °C higher under sun and 1.8 °C higher in shade as compare to recorded city's average air temperature. Riders reported exhaustion, reduced productivity, income loss, and negative impacts on social wellbeing during hot days. For mitigation riders relied on strategies like staying hydrated and taking breaks from work under shades. Study demonstrated higher exposure to heat for riders in megacity as compare to city's recorded temperature. This led to reduced productivity and income losses, emphasizing need for urgent initiatives to safeguard riders' well-being.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air pollution dynamics in Fortaleza, Brazil: Exploring the interplay of traffic and high-rise development","authors":"","doi":"10.1016/j.uclim.2024.102176","DOIUrl":"10.1016/j.uclim.2024.102176","url":null,"abstract":"<div><div>The increasing concern over urban air quality has spurred research into atmospheric pollution, particularly focusing on the substantial influence of vehicle traffic on emissions. This study aimed to elucidate the variation of air pollutants in distinct areas of Fortaleza, a large metropolis in Brazil, utilizing a cost-effective sensor for data collection. Primary data on air pollutants, meteorological conditions, and vehicular traffic were collected at eleven locations within the city. Urban elements such as building height and road classification were also considered. Surprisingly, pollution levels did not correlate directly with traffic volume but demonstrated stronger associations with urban and meteorological factors that affect air circulation and pollutant dispersion. Notably, fine particulate matter (PM2.5) exhibited lesser susceptibility to urban characteristics compared to carbon dioxide, with meteorological variables exerting a more pronounced influence. Furthermore, a correlation emerged between elevated pollution levels and areas characterized by urban canyons, highlighting the pivotal role of urban planning in pollution alleviation. The use of a low-cost sensor proved effective in measuring atmospheric pollution and meteorological data yet expanding the study to include additional variables such as wind speed and direction, as well as road quality attributes, is essential for a comprehensive understanding of this complex phenomenon.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analysis of polyaromatic hydrocarbons in road dust: An emerging threat in urban environment","authors":"","doi":"10.1016/j.uclim.2024.102172","DOIUrl":"10.1016/j.uclim.2024.102172","url":null,"abstract":"<div><div>Road dust (RD) has emerged as a significant contributor to air pollution in urban areas. It serves as a major reservoir for various contaminants including highly toxic heavy metals and polyaromatic hydrocarbons (PAHs). Therefore, road dust poses threats not only to the environment but also human health, particularly to commuters and residents near roadsides. The abrasion of tyres and the release of carbonaceous materials from vehicle emissions further increases the toxicity of road dust. This study presents a comprehensive review of sources and fate of PAHs in road dust as well as their toxicity in the environment. We have used the Web of Science database from 1989 to 2023. Our study suggests that this research topic has seen a substantial increase in investigations with a rate of ∼40 % since 2008. However, despite an increase in urbanization and industrialization and high toxicity of PAHs in RD, research in developing countries is still limited, primarily due to an inadequate funding and lack of technical advancements. Although atmospheric concentrations of PAHs have declined in developed countries, largely due to the implementation of strict emission standards and air quality regulations, adoption of advanced cleaner fuels and technologies, the demand for transport and energy is more likely to increase in developing countries in the future. Therefore, the study emphasizes the importance of promoting research on RD (size, composition and toxicity) pollution to address and mitigate the impact of PAHs on human health and the environment. Our study highlights that there is a strong need for more research on trade-off between emission and control measures to regulate RD emissions as well as toxic carcinogens including PAHs and heavy metals in urban environment.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing methane emissions in five Indian cities using TROPOMI data from sentinel-5 precursor satellite","authors":"","doi":"10.1016/j.uclim.2024.102174","DOIUrl":"10.1016/j.uclim.2024.102174","url":null,"abstract":"<div><div>Methane (CH₄) is a greenhouse gas, and studying it is essential due to its high global warming potential and significant role in climate change. The present study investigated the spatiotemporal variations of CH₄ in five cities (i.e., Ahmedabad, Bengaluru, Delhi, Hyderabad, and Jaipur) of India to better understand its distribution and trends from 2019 to 2023. The study also investigated relationship between CH₄ and various parameters such as land surface temperature, spectral indices, meteorological variables, heat flux, and urbanization parameters. In Ahmedabad, it was observed that CH₄ was most sensitive to change in Northward Turbulent Surface Stress (NWSS). Jaipur demonstrated a very strong correlation with eastward wind (<em>r</em> = −0.747), while Ahmedabad exhibited a strong correlation with NWSS (<em>r</em> = 0.828) and temperature at 2 m (<em>r</em> = 0.826). The study categorized CH₄ concentrations across different land use and land cover classes, revealing distinct spatial patterns of CH₄ distribution within urban environments. Spatial autocorrelation analysis showed that Jaipur displayed the highest clustering of CH₄ values. This study provides insights that could help policymakers and urban planners implement effective measures to reduce CH₄ emissions, supporting efforts to mitigate climate change and its impacts.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of 1 ×1 km gridded emission inventory for air quality assessment and mitigation strategies from open biomass burning in Karnataka, India","authors":"","doi":"10.1016/j.uclim.2024.102168","DOIUrl":"10.1016/j.uclim.2024.102168","url":null,"abstract":"<div><div>In this work, we have developed a high-resolution (1 ×1 km grid) emission inventory of greenhouse gases and air pollutants from open biomass burning (OBB) in Karnataka for 2000, 2005, 2010, 2015, 2020, and 2022. Secondary and field datasets were used to validate the emission inventories. The GIS-based statistical model and activity data were used to estimate greenhouse and air pollutant gas emissions from OBB (Forest, grassland, and crop fires). The uncertainty analysis of the emissions were done using the Monte Carlo Simulation (MCS) model and Low Emission Analysis Platform (<span><span>LEAP</span></span>) tool was used for projecting the emissions to 2050 based on the annual average growth rate. According to our results, the total OBB burned areas (%) in Karnataka during the aforementioned years were 24.43, 15.69, 15.95, 11.41, 26.73, and 5.78. The results showed that total annual average OBB emissions in Karnataka for 2000–2022 in Gg were SO₂ (6.67), NO_x (9.48), NH₃(9.80), CO (670.12), OC (59.78), BC (5.09), CO₂ (11071 .11), CH₄(33.68), PM₁₀(84.29), PM_2.5(81.08), NMVOC (74.13), and NO₂ (4.80) respectively. The districts of Kalburgi, Raichur, Bagalkot, Uttara Kannada, and Shivamogga have the highest emissions from OBB in Karnataka from 2000 to 2022. The emission uncertainty results showed ±26.92, ±28.17, and ±30.27 % for the crop, grassland, and forest fires, respectively. Under the business-as-usual (BAU) scenarios, the CH₄ emissions from forest, grassland, and crop fires are projected at 8823, 2.64, and 5262 metric tonnes by 2030 and 58046, 10, and 30700 metric tonnes by 2050, respectively. The developed high-resolution inventories are the most up-to-date surface emission datasets with hotspots in Karnataka from OBB emission. National Clean Air Programme (NCAP) and India’s Net-Zero Emission target by 2070, our high-resolution emission inventories and mitigation strategies may be helpful for air quality monitoring, health benefits analysis, and policy-making studies in Karnataka, India.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of ambient temperature on chronic obstructive pulmonary disease (COPD) mortality in highly polluted region","authors":"","doi":"10.1016/j.uclim.2024.102163","DOIUrl":"10.1016/j.uclim.2024.102163","url":null,"abstract":"<div><div>The Global Burden of Disease (GBD) studies have established a clear connection between ambient air pollution, extreme temperatures, and an increased risk of mortality from chronic obstructive pulmonary disease (COPD). However, limited research has been conducted on the relationship between ambient temperature and COPD mortality in heavily polluted regions in China. This particular study examines the above effect using weekly data from the Yangtze River Delta area from 2013 to 2017. A Poisson generalized linear regression model with a distributed lag non-linear model (DLNM) was employed to assess the risk of COPD mortality associated with temperature and lag effects on a weekly basis. The analysis showed that colder temperatures posed a higher risk, with extreme cold temperatures (3 °C) having a significant impact on COPD mortality. On the other hand, extreme hot temperatures (32 °C) did not demonstrate significant short-term effects. The study also revealed that females and individuals already suffering from COPD were more susceptible to the adverse effects of extreme temperatures. These findings provide valuable insights into the association between ambient temperature and cause-specific mortality risk in highly polluted regions, which can help in managing the disease burden related to climate change, including extreme weather events such as heat waves and cold waves.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The urban wind island from a three-dimensional perspective","authors":"","doi":"10.1016/j.uclim.2024.102164","DOIUrl":"10.1016/j.uclim.2024.102164","url":null,"abstract":"<div><div>The Urban Wind Island (UWI), a small but persistent positive mean boundary-layer wind anomaly over the city as a whole, has previously been revealed using a simplified conceptual model of the convective atmospheric boundary layer. This study extends the UWI research into less idealised cases by using the three-dimensional WRF mesoscale model for Amsterdam (The Netherlands) and its surroundings, at 500 m grid spacing. Two summers of forecast results for in total 173 days are used to identify whether the UWI persists in a three-dimensional modelling environment, and which conditions are optimal for its formation and persistence. In order to focus only on wind modified by surface processes, large-scale influences which modify wind speed, such as frontal passages, are identified and eliminated from the dataset. We then find that a positive UWI is present roughly half the time, with an order of magnitude that is similar to the previous work (<span><math><mo>∼</mo></math></span> 0.2–0.5 <span><math><msup><mi>ms</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></math></span>). In addition we find an evening UWI that is caused by the delayed onset of the transition from an unstable to a stable or a neutral boundary layer in the urban area, while the rural area is already stable and calm.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cities and climate change in developing countries","authors":"","doi":"10.1016/j.uclim.2024.102169","DOIUrl":"10.1016/j.uclim.2024.102169","url":null,"abstract":"<div><div>An increasing proportion of greenhouse gas emissions is coming from urban areas, particularly in developing countries with low- and middle-income economies. While the major challenge for transitions into climate-friendly urban areas in developed countries is the reduction of their consumption footprints, the key factor for advancing the urban climate agenda in developing countries is the link between climate change and the achievement of various Sustainable Development Goals, as these countries struggle with “old problems,” including the provision of basic services and the need to raise incomes. Thus, the contributions of the articles of this special issue explore two main aspects: the understanding of the impacts of climate change in its various dimensions, and the responses and solutions cities have adopted to tackle climate change.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal change of PM2.5 concentration in Beijing-Tianjin-Hebei and its prediction based on machine learning","authors":"","doi":"10.1016/j.uclim.2024.102167","DOIUrl":"10.1016/j.uclim.2024.102167","url":null,"abstract":"<div><div>For decades, PM_2.5 (a type of fine particulate matter) in large urban areas has had a profound negative impact on human health. In this study, spatiotemporal analysis and four machine learning methods (XGBoost, ANN, CNN and MLR) were used to assess the changes and drivers of PM_2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) from 2016 to 2019 based on 68 stations. The results indicated a significant decrease in PM_2.5 concentrations in BTH region (average decrease of 7.69 μg/m³/yr), especially in the southwest region where pollution is the most serious, and the overall annual average still exceeded the national standard. In spatiotemporal modeling, XGBoost effectively captured the spatial characteristics of PM_2.5 pollution and achieved the most robust prediction in general (RMSE = 22.11 μg/m³, MAE = 15.18 μg/m³, R² = 0.64). The SHapley Additive exPlanations (SHAP)-based global and local driving analyses revealed that CO had the greatest relative impact on PM_2.5 (52.46 %), while NO₂ and SO₂ were also important driving factors, with variable importance values of 10.68 % and 6.01 %, respectively. Moreover, temperature and surface humidity are key meteorological drivers of the formation and development of PM_2.5 pollution. It is also worth noting that topography is an important geographic background for the formation of haze in the BTH region, which may induces air pollution under unfavorable meteorological conditions and hindering the improvement of air quality under favorable meteorological conditions. The results of this study deepen our understanding of air pollution and its driving factors in important urban agglomerations in China.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal distribution of cooling effects from urban-scale rooftop mitigation strategies during high-temperature weather—A case study of the coastal Metropolis Tokyo","authors":"","doi":"10.1016/j.uclim.2024.102155","DOIUrl":"10.1016/j.uclim.2024.102155","url":null,"abstract":"<div><div>Rooftop mitigation strategies (RMSs) can alleviate extreme heat in highly urbanized cities under global warming. In this study, gridded urban canopy parameters for Tokyo, a coastal metropolis, were integrated into the Weather Research and Forecasting model, coupled with a multilayer urban canopy model. The effects of rooftop photovoltaic (PV) panels, sedum green roofs (GRs), and grass GRs on the urban thermal environment during high-temperature days were then analyzed. PV panels, sedum GR, and grass GR with 50 % coverage achieved the most significant reductions in regional average pedestrian-level air temperatures at 2 PM, 10 AM, and 12 PM, respectively, with reductions of 0.10 °C, 0.11 °C, and 0.13 °C. The daily peak of regional maximum cooling effects for all RMSs were observed around 2 PM, reaching 0.25 °C, 0.25 °C, and 0.30 °C, respectively. Despite the daytime cooling effect, both GRs increased heat stress, which was particularly noticeable in grass GRs due to their stronger evaporative capacity, resulting in an increase in WBGT of up to 0.15 °C in approximately 75 % of the study areas. Additionally, the impacts of RMSs in coastal areas extended to the northwestern hinterland, indicating a non-local pattern influenced by sea-breeze advection. Furthermore, under high-temperature conditions, the cooling effect of GRs at midday increased linearly with background temperature.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}