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An accurate emission inventory is a crucial part of air pollution management and is essential for air quality modelling. One source in an emission inventory, an industrial source, has been known with high uncertainty in both location and magnitude in China. In this study, a new reallocation method based on blue-roof industrial buildings was developed to replace the conventional method of using population density for the Chinese emission development. The new method utilized the zoom level 14 satellite imagery (i.e. Google®) and processed it based on hue, saturation, and value (HSV) colour classification to derive new spatial surrogates for province-level reallocation, providing more realistic spatial patterns of industrial PM2.5 and NO2 emissions in China. The WRF-CMAQ-based PATH-2016 model system was then applied with the new processed industrial emission input in the MIX inventory to simulate air quality in the Greater Bay Area (GBA) area (formerly called Pearl River Delta, PRD). In the study, significant root mean square error (RMSE) improvement was observed in both summer and winter scenarios in 2015 when compared with the population-based approach. The average RMSE reductions (i.e. 75 stations) of PM2.5 and NO2 were found to be 11 µg m−3 and 3 ppb, respectively. Although the new method for allocating industrial sources did not perform as well as the point- and area-based industrial emissions obtained from the local bottom-up dataset, it still showed a large improvement over the existing population-based method. In conclusion, this research demonstrates that the blue-roof industrial allocation method can effectively identify scattered industrial sources in China and is capable of downscaling the industrial emissions from regional to local levels (i.e. 27 to 3 km resolution), overcoming the technical hurdle of ∼ 10 km resolution from the top-down or bottom-up emission approach under the unified framework of emission calculation.

An initial condition that closely represents the true atmospheric state can minimize errors that propagate into the future, and could theoretically lead to improvements in the forecast. This study aims to evaluate and understand the impacts of 3DVAR on the state-of-the-art Weather Research and Forecasting (WRF) model with a two nested domains setup. The domain configuration of the model covers China with an emphasis on Guangdong province, with a resolution of 27 km, 9 km, and 3 km. Improvements in the forecasts for the Winter and Summer season of all the domains are systematically compared and are quantified in terms of 2 m temperature, 10 m wind speed, sea level pressure, and 2 m relative humidity. The results show that 3DVAR provides significant improvements in the winter case and surprisingly improvements were also found after the 48 h of the forecast. Evaluations of performance of 3DVAR in different domains and between two different seasons were done to further understand the reasons behind the discrepancies.

City air quality monitoring (AQM) network are typically sparsely distributed due to high operation costs. It is of the question of how well it can reflect public health risks to air pollution given the diversity and heterogeneity in pollution, and spatial variations in population density. Combing high-resolution air quality model, spatial population distribution and health risk factors, we proposed a population-health based metric for AQM representativeness. This metric was demonstrated in Hong Kong using hourly modelling data of PM10, PM2.5, NO2 and O3 in 2019 with grid cells of 45m * 48m. Individual and total hospital admission risks (%AR) of these pollutants were calculated for each cell, and compared with those calculated at 16 monitoring sites using the similarity frequency (SF) method. AQM Representativeness was evaluated by SF and a population-health based network representation index (PHNI), which is population-weighted SF over the study-domain. The representativeness varies substantially among sites as well as between population- and area-based evaluation methods, reflecting heterogeneity in pollution and population. The current AQM network reflects population health risks well for PM10 (PHNI = 0.87) and PM2.5 (PHNI = 0.82), but is less able to represent risks for NO2 (PHNI = 0.59) and O3 (PHNI = 0.78). Strong seasonal variability in PHNI was found for PM, increasing by >11% during autumn and winter compared to summer due to regional transport. NO2 is better represented in urban than rural, reflecting the heterogeneity of urban traffic pollution. Combined health risk (%ARtotal) is well represented by the current AQM network (PHNI = 1), which is more homogenous due to the dominance and anti-correlation of NO2 and O3 related %AR. The proposed PHNI metric is useful to compare the health risk representativeness of AQM for individual and multiple pollutants and can be used to compare the effectiveness of AQM across cities.

The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, −0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between −9.41 °C and −13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (, Graphical abstract Unlabelled Image, Highlights • A mechanism-based parameterisation scheme was developed for transmission rate. • Scale of population migration from Wuhan was incorporated. • Population density had a non-linear (linearity index, 0.9) impact on disease spread. • Transmission rate shows a negative and exponential temperature dependence. • COVID-19 mitigation in densely populated and cold regions will be a great challenge.

Urbanization is one of the most significant contributing factors to anthropogenic climate change. However, a lack of projected city land use data has posed significant challenges to factoring urbanization into climate change modeling. Thus, the results from current models may contain considerable errors in estimating future climate scenarios. The Pearl River Delta region was selected as a case study to provide insight into how large-scale urbanization and different climate change scenarios impact the local climate. This study adopts projected land use data from freely available satellite imagery and applies dynamic simulation land use results to the Weather Research and Forecasting Model (WRF). The simulation periods cover the summer periods in 2010 and 2029&ndash, 2031, the latter of which is averaged to represent the year 2030. The WRF simulation used the observed local climate conditions in 2010 to represent the current scenario and the projected local climate changes for 2030 as the future scenario. Under all three future climate change scenarios, the warming trend is prominent (around 1&ndash, 2 &deg, C increase), with a widespread reduction in wind speed in inland areas (1&ndash, 2 ms&minus, 1). The vulnerability of human health to thermal stress was evaluated by adopting the wet-bulb globe temperature (WBGT). The results from the future scenarios suggest a high public health risk due to rising temperatures in the future. This study provides a methodology for a more comprehensive understanding of future urbanization and its impact on regional climate by using freely available satellite images and WRF simulation tools. The simulated temperature and WBGT results can serve local governments and stakeholders in city planning and the creation of action plans that will reduce the potential vulnerability of human health to excessive heat.

The Greater Bay Area (GBA) of China is experiencing a high level of exposure to outdoor PM2.5 pollution. The variations in the exposure level are determined by spatiotemporal variations in the PM2.5 concentration and population. To better guide public policies that aim to reduce the population exposure level, it is essential to explicitly decompose and assess the impacts of different factors. This study took advantage of high-resolution satellite observations to characterize the long-term variations in population exposure to outdoor PM2.5 for cities in the GBA region during the three most-recent Five-Year Plan (FYP) periods (2001–2015). A new decomposition method was then used to assess the impact of PM2.5 variations and demographic changes on the exposure variation. Within the decomposition framework, an index of pollution-population-coincidence–induced PM2.5 exposure (PPCE) was introduced to characterize the interaction of PM2.5 and the population distribution. The results showed that the 15-year average PPCE levels in all cities were positive (e.g., 6 µg/m3 in Guangzhou), suggesting that unfavorable city planning had led to people dwelling in polluted areas. An analyses of the spatial differences in PM2.5 changes showed that urban areas experienced a greater decrease in PM2.5 concentration than did rural areas in most cities during the 11th (2006–2010) and 12th (2011–2015) FYP periods. These spatial differences in PM2.5 changes reduced the PPCE levels of these cities and thus reduced the exposure levels (by as much as -0.58 µg/m3/year). The population migration resulting from rapid urbanization, however, increased the PPCE and exposure levels (by as much as 0.18 µg/m3/year) in most cities during the three FYP periods considered. Dongguan was a special case in that the demographic change reduced the exposure level because of its rapid development of residential areas in cleaner regions adjacent to Shenzhen. The exposure levels in all cities remained high because of the high mean PM2.5 concentrations and their positive PPCE. To better protect public health, control efforts should target densely populated areas and city planning should locate more people in cleaner areas.

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.

The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs) as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones (LCZ) with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC) tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC) to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells.

The World Urban Database and Access Portal Tools (WUDAPT) is an international community-based initiative to acquire and disseminate climate relevant data on the physical geographies of cities for modeling and analysis purposes. The current lacuna of globally consistent information on cities is a major impediment to urban climate science toward informing and developing climate mitigation and adaptation strategies at urban scales. WUDAPT consists of a database and a portal system; its database is structured into a hierarchy representing different levels of detail, and the data are acquired using innovative protocols that utilize crowdsourcing approaches, Geowiki tools, freely accessible data, and building typology archetypes. The base level of information (L0) consists of local climate zone (LCZ) maps of cities; each LCZ category is associated with a range of values for model-relevant surface descriptors (roughness, impervious surface cover, roof area, building heights, etc.). Levels 1 (L1) and 2 (L2) will provide specific intra-urban values for other relevant descriptors at greater precision, such as data morphological forms, material composition data, and energy usage. This article describes the status of the WUDAPT project and demonstrates its potential value using observations and models. As a community-based project, other researchers are encouraged to participate to help create a global urban database of value to urban climate scientists.

Atmospheric particulate matter (PM) remains poorly understood due to the lack of comprehensive measurements at high time resolution for tracking its dynamic features and the lack of long-term observation for tracking its seasonal variability. Here, we present highly time-resolved and seasonal compositions and characteristics of non-refractory components in PM with a diameter less than 1 μm (NR-PM1) at a suburban site in Hong Kong. The measurements were made with an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) at the Hong Kong University of Science and Technology (HKUST) Air Quality Research Supersite for 4 months, with one in each season of the year. The average NR-PM1 concentration of ~ 15 μg m−3 is higher than those AMS measurements made in South Korea and Japan, but lower than those in North China, the Yangtze River Delta and the nearby Pearl River Delta. The seasonal dependence of the total NR-PM1 monthly averaged concentrations was small, but that of the fractions of the species in NR-PM1 was significant. Site characteristic plays an important role in the relative fractions of species in NR-PM1 and our results are generally consistent with measurements at other non-urban sites in this regard. Detailed analyses were conducted on the AMS data in the aspects of (1) species concentrations, (2) size distributions, (3) degree of oxygenation of organics, and (4) positive matrix factorization (PMF)-resolved organic factors in a seasonal context, as well as with air mass origin from back-trajectory analysis. Sulfate had the highest fraction in NR-PM1 (> 40%), and the surrogates of secondary organic species – semi-volatile oxygenated organic aerosol (SVOOA) and low-volatility oxygenated organic aerosol (LVOOA) – prevailed (~ 80%) in the organic portion of NR-PM1. Local contributions to the organic portion of NR-PM1 at this suburban site was strongly dependent on season. The hydrocarbon-like organic aerosol (HOA) factor related to local traffic emissions contributed > 10% to organic aerosols in spring and summer but only 6–7% in autumn and winter. The cooking organic aerosol (COA) factor contributed > 10% to organic aerosols in winter. With the aid of highly time-resolved data, diurnal patterns of the degree of oxygenation of organic aerosols were used to determine the sources and formation processes of the least understood organic portion of PM. The oxygen-to-carbon atomic ratio (O : C) and average carbon oxidation state OS C) showed little variation in autumn and winter, when the long-range transport of oxidized organics dominated, whereas they peaked in the afternoon in spring and summer, when locally produced secondary organic aerosol prevailed. Air mass origin, in contrast, had a strong influence on both NR-PM1 concentrations and the fractions of species in NR-PM1. The findings of the current study provide a better understanding of the role of air mass origin in the seasonal characteristics of the PM composition and the relative importance of local vs. transported organic aerosols in this region.

The ability of numerical simulations to predict typhoons has been improved in recent decades. Although the track prediction is satisfactory, the intensity prediction is still far from adequate. Vortex initialization is an efficient method to improve the estimations of the initial conditions for typhoon forecasting. In this paper, a new vortex initialization scheme is developed and evaluated. The scheme requires only observational data of the radius of maximum wind and the max wind speed in addition to the global analysis data. This scheme can also satisfy the vortex boundary conditions, which means that the vortex is continuously merged into the background environment. The scheme has a low computational cost and has the flexibility to adjust the vortex structure. It was evaluated with 3 metrics: track, center sea-level pressure (CSLP), and maximum surface wind speed (MWSP). Simulations were conducted using the WRF-ARW numerical weather prediction model. Super and severe typhoon cases with insufficiently strong initial MWSP were simulated without and with the vortex initialization scheme. The simulation results were compared with the 6-hourly observational data from Hong Kong Observatory (HKO). The vortex initialization scheme improved the intensity (CSLP and MWSP) prediction results. The scheme was also compared with other initialization methods and schemes.

The impact of nitrous acid (HONO) chemistry on regional ozone and particulate matter in Pearl River Delta region was investigated using the community multiscale air quality (CMAQ) modeling system and the CB05 mechanism. Model simulations were conducted for a ten-day period in October 2004. Compared with available observed data, the model performance for NOx, SO2, PM10, and sulfate is reasonably good; however, predictions of HONO are an order of magnitude lower than observed data. The CB05 mechanism contains several homogenous reactions related to HONO. To improve the model performance for HONO, direct emissions, two heterogeneous reactions, and two surface photolysis reactions were incorporated into the model. The inclusion of the additional formation pathways significantly improved simulated HONO compared with observed data. The addition of HONO sources enhances daily maximum 8-hour ozone by up to 6 ppbV (8%) and daily mean PM2.5by up to 17 ug/m3(12%). They also affected ozone control strategy in Pearl River Delta region.

The objectives of this study are to combine historical observations and state-of-the-art numerical models (MM5/CALMET system) to map the spatial distribution of wind resources in high resolution, and to help foster a deeper understanding of the wind power potential over southern China (Guangdong). Hourly wind fields were simulated for three entire years (2004-2006). It found that almost 70% of the time, the wind speed along the coast of Guangdong is over 5 m/s, which is deemed a baseline magnitude for typical wind turbines. Spatial plots of the wind speed and power and their variations over Guangdong Province for the three years are also presented.